The data presented below represent the predicted number of people per ~100 m pixel as estimated using the random forest (RF) model as described in Stevens, et al. (In Press). The following pages contain a description of the RF model and its covariates, their sources and any metadata collected for each covariate. The prediction weighting layer is used to dasymetrically redistribute the census counts and project counts to match estimated populations based on UN estimates for the final population maps provided by AfriPop, AsiaPop and AmeriPop.
These data are the population density values used to estimate the RF model used to create the prediction weighting layer you see above. Values represent population density as measured by people per hectare and calculated from population counts within each census unit. These values are used as the dependent variable during model estimation.
Folder: Census
File Name: KEN_census_1999_sublocations_topo.shp
Source: Kenya National Bureau of Statistics, acquired by Tatem, et al. for use in AfriPop data products.
Description: These census data were acquired for use as a disaggregation layer for more-recent census data for AfriPop. It is used here on its own to produce a disaggregated population map for 1999 because it is the finest level census data available. Required fields for map production are ADMINID and ADMINPOP.
Class: polygon
Derived Covariates:
area, buff, zones,
class : SpatialPolygonsDataFrame
nfeatures : 6624
extent : -66764, 823501, -517009, 605783 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 50
These output and figures outline the estimated RF model that is used to predict the population density weighting layer. The model is fitted to the population density values for the preceding census data using covariates aggregatedfrom the ancillary data sources summarized following the model diagnostics.
Call:
randomForest(x = x_data, y = y_data, ntree = popfit$ntree, mtry = popfit$mtry, nodesize = length(y_data)/1000)
Type of random forest: regression
Number of trees: 500
No. of variables tried at each split: 8
Mean of squared residuals: 0.67
% Var explained: 83
Folder: Landcover
File Name: KEN_gc_reclass_0.0008333_rurb_8bit.img
Source: GlobCover, 300m
Description: Landcover from the GlobCover product, reclassified to match AfriPop coding and eventually broken down into binary classifications by aggregated land cover type (see Linard, et al., 2010 and Gaughan, et al. 2013 for category information).
Class: raster
Derived Covariates:
prp011, cls011, dst011, prp040, cls040, dst040, prp130, cls130, dst130, prp140, cls140, dst140, prp150, cls150, dst150, prp160, cls160, dst160, prp190, cls190, dst190, prp200, cls200, dst200, prp210, cls210, dst210, prp230, cls230, dst230, prp240, cls240, dst240, prp250, cls250, dst250, prpBLT, clsBLT, dstBLT,
class : RasterLayer
dimensions : 11263, 8911, 100364593 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66765, 824335, -519218, 607082 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\Landcover\Derived\landcover.tif
names : landcover
values : 0, 240 (min, max)
attributes :
ID OID Value Count
from: 0 0 11 19254933
to : 9 9 240 8562
Folder: NPP
File Name: KEN_gc_reclass_0.0008333_rurb_8bit.img
Source: United States Geological Survey (USGS)
Description: MODIS 17A3 version-55 derived estimates of net primary productivity for the year 2010, estimated for 1km pixel sizes and subset and resampled to match the available land cover and final population map output requirements.
Class: raster
Derived Covariates:
,
class : RasterLayer
dimensions : 11263, 8911, 100364593 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66765, 824335, -519218, 607082 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\NPP\Derived\npp.tif
names : npp
values : 0, 22341 (min, max)
attributes :
ID Rowid COUNT
from: 0 0 11089043
to : 22341 19433 90
Folder: Lights
File Name: DEFAULT: VIIRS 2012
Source: http://ngdc.noaa.gov/eog/viirs/download_viirs_ntl.html
Description: These 'Lights at Night' data were derived from imagery collected by the Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) sensor. Data were collected in 2012 on moonless nights and though background noise associated with fires, gas-flares, volcanoes or aurora have not been removed it represents the best-available data for night-time light production.
Class: raster
Derived Covariates:
,
class : RasterLayer
dimensions : 11264, 8912, 100384768 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66865, 824335, -519218, 607182 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\Lights\Derived\lights.tif
names : lights
values : -0.36, 182 (min, max)
Folder: Temp
File Name: DEFAULT: BIO1
Source: http://www.worldclim.org/current
Description: WorldClim/BioClim 1950-2000 mean annual precipitation (BIO12) and mean annual temperature (BIO1) estimates (Hijmans et al., 2005) were downloaded, mosaicked and subset to match the extent of our land cover data for the mapping of this region.
Class: raster
Derived Covariates:
,
class : RasterLayer
dimensions : 11264, 8912, 100384768 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66865, 824335, -519218, 607182 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\Temp\Derived\temp.tif
names : temp
values : -50, 296 (min, max)
attributes :
ID OID Value Count
from: 0 0 -290 1
to : 609 609 320 31
Folder: Precip
File Name: DEFAULT: BIO12
Source: http://www.worldclim.org/current
Description: WorldClim/BioClim 1950-2000 mean annual precipitation (BIO12) and mean annual temperature (BIO1) estimates (Hijmans et al., 2005) were downloaded, mosaicked and subset to match the extent of our land cover data for the mapping of this region.
Class: raster
Derived Covariates:
,
class : RasterLayer
dimensions : 11264, 8912, 100384768 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66865, 824335, -519218, 607182 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\Precip\Derived\precip.tif
names : precip
values : 172, 2624 (min, max)
attributes :
ID OID Value Count
from: 0 0 0 1157797
to : 9586 9586 11401 1
Folder: Roads
File Name:
Source: Kenya Bureau of Statistics, acquired by Andrew J. Tatem
Description: This is a detailed road layer available country-wide and provided by the Kenya Beureau of Statistics to project members.
Class: linear
Derived Covariates:
dst,
class : SpatialLinesDataFrame
nfeatures : 148897
extent : -62788, 818799, -515486, 585666 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 51
Folder: Rivers
File Name: DEFAULT: hydro/watrcrsl
Source: National Geospatial-Intelligence Agency (NGA), http://geoengine.nga.mil/geospatial/SW_TOOLS/NIMAMUSE/webinter/rast_roam.html
Description: The VMAP0 data area downloaded as separate files, grouped roughly by continent, and merged into individual shapefiles for subsetting and further processing for population mapping efforts. These data were obtained directly from the original VMAP0 data sources provided by the NGA and pre-processed using Military Analyst in ArcGIS 10.0.
Class: linear
Derived Covariates:
dst,
class : SpatialLinesDataFrame
nfeatures : 3008
extent : -68015, 828354, -519028, 610624 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 8
Folder: Populated
File Name:
Source: Tatem, A. J., Noor, A. M., & Hay, S. I. (2004). Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery. Remote Sensing of Environment, 93(1-2), 42–52. doi:10.1016/j.rse.2004.06.014
Description: These data were created as described in the Tatem, et al. paper (2004) and derived from Landsat Thematic Mapper ™ and Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) imagery at a 40 m nominal resolution.
Class: polygon
Derived Covariates:
merged, cls, dst, prp,
class : SpatialPolygonsDataFrame
nfeatures : 1660
extent : -47506, 818239, -515779, 466985 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 1
Folder: Waterbodies
File Name: DEFAULT: hydro/watrcrsl
Source: National Geospatial-Intelligence Agency (NGA), http://geoengine.nga.mil/geospatial/SW_TOOLS/NIMAMUSE/webinter/rast_roam.html
Description: The VMAP0 data area downloaded as separate files, grouped roughly by continent, and merged into individual shapefiles for subsetting and further processing for population mapping efforts. These data were obtained directly from the original VMAP0 data sources provided by the NGA and pre-processed using Military Analyst in ArcGIS 10.0.
Class: polygon
Derived Covariates:
cls, dst, prp,
class : SpatialPolygonsDataFrame
nfeatures : 275
extent : -76649, 784380, -505933, 554558 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 8
Folder: Protected
File Name: DEFAULT: WDPAfgdb_Sept2012.gdb
Source: World Database on Protected Areas, Downloaded September, 2012, UNEP, http://www.wdpa.org, http://protectedplanet.net
Description: These data are compiled by UNEP and distributed via the Protected Planet website. All protected areas were downloaded regardless of International Union for Conservation of Nature (IUCN) or any other designation, so they include sanctuaries, national parks, game reserves, World Heritage Sites, etc.
Class: polygon
Derived Covariates:
cls, dst, prp,
class : SpatialPolygonsDataFrame
nfeatures : 213
extent : -60520, 794358, -524625, 615783 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 26
Folder: Elevation
File Name: DEFAULT: Void-Filled DEM.gdb
Source: HydroSHEDS Void-Filled DEM (Lehnert, et al., 2006), http://hydrosheds.cr.usgs.gov/dataavail.php
Description: The HydroSHEDS data are the result of an effort to provide a globally consistent dataset consisting of NASA's Shuttle Radar Topography Mission (SRTM) data and have been processed, void-filled and corrected for use at large scales.
Class: raster
Derived Covariates:
, slope,
class : RasterLayer
dimensions : 11264, 8912, 100384768 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66865, 824335, -519218, 607182 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\Elevation\Derived\elevation.tif
names : elevation
values : -18, 5875 (min, max)
Folder: Built
File Name: ksm-imagine3_100m.img
Source: Tatem, A. J., Noor, A. M., & Hay, S. I. (2004). Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery. Remote Sensing of Environment, 93(1-2), 42–52. doi:10.1016/j.rse.2004.06.014
Description: This raster layer represents built land cover as derived from a combination of Landsat Thematic Mapper ™ imagery and Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) data.
Class: raster
Derived Covariates:
prp, cls, dst,
class : RasterLayer
dimensions : 11264, 8912, 100384768 (nrow, ncol, ncell)
resolution : 100, 100 (x, y)
extent : -66865, 824335, -519218, 607182 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=37 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
data source : D:\Documents\Graduate School\Research\Population\Data\RF\data\KEN\Built\Derived\built_cls.tif
names : built_cls
values : 0, 1 (min, max)
attributes :
ID OID Value Count
0 0 0 134192546
1 1 1 192862
Folder: Clinics
File Name: noor_clinics_type3.shp
Source: Noor, A. M., Alegana, V. A., Gething, P. W., & Snow, R. W. (2009). A spatial national health facility database for public health sector planning in Kenya in 2008. International Journal of Health Geographics, 8, 13. doi:10.1186/1476-072X-8-13
Description: These data were derived from those acquired by and described by Noor, et al. (2009). They represent point locations for major health-related points of interest within the Kenyan national boundary. Clinics, dispensaries and hospitals were separated into individual datasets from the original shapefile provided by Noor, et al.
Class: point
Derived Covariates:
prp, cls, dst,
class : SpatialPointsDataFrame
nfeatures : 934
extent : 34, 42, -4.7, 5.4 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 9
Folder: HDispensaries
File Name: noor_dispensaries_type4-6.shp
Source: Noor, A. M., Alegana, V. A., Gething, P. W., & Snow, R. W. (2009). A spatial national health facility database for public health sector planning in Kenya in 2008. International Journal of Health Geographics, 8, 13. doi:10.1186/1476-072X-8-13
Description: These data were derived from those acquired by and described by Noor, et al. (2009). They represent point locations for major health-related points of interest within the Kenyan national boundary. Clinics, dispensaries and hospitals were separated into individual datasets from the original shapefile provided by Noor, et al.
Class: point
Derived Covariates:
prp, cls, dst,
class : SpatialPointsDataFrame
nfeatures : 3711
extent : 34, 42, -4.7, 5.4 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 9
Folder: Hospitals
File Name: noor_hospitals_type1-2.shp
Source: Noor, A. M., Alegana, V. A., Gething, P. W., & Snow, R. W. (2009). A spatial national health facility database for public health sector planning in Kenya in 2008. International Journal of Health Geographics, 8, 13. doi:10.1186/1476-072X-8-13
Description: These data were derived from those acquired by and described by Noor, et al. (2009). They represent point locations for major health-related points of interest within the Kenyan national boundary. Clinics, dispensaries and hospitals were separated into individual datasets from the original shapefile provided by Noor, et al.
Class: point
Derived Covariates:
prp, cls, dst,
class : SpatialPointsDataFrame
nfeatures : 299
extent : 34, 42, -4.5, 4.3 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 9
Folder: Schools
File Name: KEN_School.shp
Source: Kenya Open Data. (2013). Open Kenya, Transparent Africa. Kenya Primary Schools, 2007. Retrieved May 24, 2013, from https://opendata.go.ke/Education/Kenya-Primary-Schools-2007/p452-xb7c
Description: These data represent school and education-related points of interest and were provided by the Kenya Open Data Initiative ( https://opendata.go.ke ).
Class: point
Derived Covariates:
prp, cls, dst,
class : SpatialPointsDataFrame
nfeatures : 3759
extent : -60144, 817711, -454529, 473877 (xmin, xmax, ymin, ymax)
coord. ref. : NA
nvariables : 5