GRID3 ZMB - Population v1.0

These data feature gridded population estimates (~100 m grid cells) and population estimates for specific age groups, with national coverage for Zambia. The zipfiles contain the following files: ZMB_population_v1_0_gridded.tif This geotiff raster contains estimates of total population size for each approximately 100m grid cell (0.0008333 decimal degrees grid) across Zambia. The values are the mean of the posterior probability distribution for the predicted population size in each grid cell. NA values represent areas that were mapped as unsettled according to building footprints data [8]. Note: This raster is accompanied by one ancillary file that contains metadata (ZMB_population_v1_0_gridded.tif.xml). ZMB_population_v1_0_uncertainty.tif This geotiff raster contains estimates of uncertainty in the population estimates within each approximately 100m grid cell across Zambia. The uncertainty values are the difference between the upper and lower 95% credible intervals of the posterior prediction divided by the mean of the posterior prediction: (upper – lower)/mean. These numbers provide a comparable measure of uncertainty in population estimates across the country. Uncertainty estimates cannot be summed across grid cells to produce an uncertainty measure for a multi-cell area. Uncertainty for multiple cells can be calculated using the cells’ posterior predictions. Note: This raster is accompanied by one ancillary file that contains metadata (ZMB_population_v1_0_uncertainty.tif.xml). ZMB_population_v1_0_agesex.zip This zip file contains 40 rasters in geotiff format. Each raster provides gridded population estimates for an age-sex group. We provide 36 rasters for the commonly reported age-sex groupings of sequential age classes for males and females separately. These are labelled with either an “m” (male) or an “f” (female) followed by the number of the first year of the age class represented by the data. “f0” and “m0” are population counts of under 1 year olds for females and males, respectively. “f1” and “m1” are population counts of 1 to 4 year olds for females and males, respectively. Over 4 years old, the age groups are in five year bins labelled with a “5”, “10”, etc. Eighty year olds and over are represented in the groups “f80” and “m80”. We provide an addition four rasters that represent demographic groups often targeted by programmes and interventions. These are “under1” (all females and males under the age of 1), “under5” (all females and males under the age of 5), “under15” (all females and males under the age of 15) and “f15_49” (all females between the ages of 15 and 49, inclusive). These data were produced using the gridded age-sex proportions from Carioli et al. [1] by multiplying the gridded population estimates(ZMB_population_v1_0_gridded.tif) by the gridded age-sex proportions which differ by region. While this data represents population counts, values contain decimals, i.e. fractions of people. This is because we do not estimate which grid cell each individual in a given age group occupies. For example, if four grid cells next to each other have values of 0.25 this indicates that there is 1 person of that age group somewhere in those four grid cells. Note, these data are operational population estimates and are not official government statistics. The downloadable Metadata provides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data Cited Contact [e-mail] for more information or gohere. Data Citation: WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. Bottom-up gridded population estimates for Zambia, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00662 CREDITS: The modelling work was led by Claire A. Dooley with support from Douglas R. Leasure. Geospatial data processing was carried out by Heather R. Chamberlain, Claire A. Dooley and Oliver Pannell. Coordination and stakeholder engagement was led by Heather R. Chamberlain and Claire A. Dooley with support from Polly Marshall. Oversight was provided by Andrew J. Tatem and Attila N. Lazar. These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office. It is implemented by Columbia University’s Center for International Earth Science Information Network (CIESIN), the United Nations Population Fund (UNFPA), WorldPop at the University of Southampton, and the Flowminder Foundation.