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.
File Name: URY_POP11.shp
Source: Instituto Nacional de Estadística and the Instituto Geográfico Militar, Uruguay, 2011
Description: These high spatial resolution census block data were attained through in-country partners for 2011.
area, buff, zones,
class : SpatialPolygonsDataFrame nfeatures : 19 extent : 366259, 866109, 6127918, 6672384 (xmin, xmax, ymin, ymax) coord. ref. : NA nvariables : 21
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.
 "Random Forest model is a merged RF model using models from:" ARG,
Call: randomForest(x = x_data, y = y_data, ntree = popfit$ntree, mtry = popfit$mtry, nodesize = length(y_data)/1000, importance = TRUE, proximity = TRUE) Type of random forest: regression Number of trees: 500 No. of variables tried at each split: 12 Mean of squared residuals: 0.58 % Var explained: 91
File Name: URY_RF_LC_Input.tif
Source: Geocover 2000 (30m), http://www.mdafederal.com/geocover
Description: Land cover from GeoCover 2000 coverage fused with Landsat-derived urban/rural built area classification to construct a single land cover dataset.
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 : RasterBrick dimensions : 5496, 5152, 28315392, 1 (nrow, ncol, ncell, nlayers) resolution : 100, 100 (x, y) extent : 360938, 876138, 6122796, 6672396 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=21 +south +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 data source : F:\WorldPop\RFmap\data\URY\Landcover\Derived\landcover.tif names : landcover min values : 11 max values : 240
File Name: DEFAULT: MODIS 17A3 2010
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 : RasterBrick dimensions : 5496, 5152, 28315392, 1 (nrow, ncol, ncell, nlayers) resolution : 100, 100 (x, y) extent : 360938, 876138, 6122796, 6672396 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=21 +south +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 data source : F:\WorldPop\RFmap\data\URY\NPP\Derived\npp.tif names : npp min values : 0 max values : 20005