Sudan - Population Counts

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Source WorldPop, University of Southampton, UK
Contributor
Date of Dataset January 01, 2000 - December 31, 2020
Updated November 24, 2020
Expected Update Frequency Every year
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Methodology

Estimated total number of people per grid-cell.m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel with country totals adjusted to match the corresponding official United Nations population estimates that have been prepared by the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat (2019 Revision of World Population Prospects).-based dasymetric redistribution The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100 developed by Stevens et al. (2015). The disaggregation was done by Maksym Bondarenko (WorldPop) and David Kerr (WorldPop), using the Random Forests population modelling R scripts (Bondarenko et al., 2020), with oversight from Alessandro Sorichetta (WorldPop).SOURCE DATA:This dataset was produced based on the 2020 population census/projection-based estimates for 2020 (information and sources of the input population data can be found here).Building footprints were provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020) and gridded building patterns derived from the datasets produced by Dooley et al. 2020.Geospatial covariates representing factors related to population distribution, were obtained from the "Global High Resolution Population Denominators Project"(OPP1134076)REFERENCES:- Stevens FR, Gaughan AE, Linard C, Tatem AJ (2015) Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data. PLoS ONE 10(2): e0107042. https://doi.org/10.1371/journal.pone.0107042- WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076).- Dooley, C. A., Boo, G., Leasure, D.R. and Tatem, A.J. 2020. Gridded maps of building patterns throughout sub-Saharan Africa, version 1.1. University of Southampton: Southampton, UK. Source of building footprints "Ecopia Vector Maps Powered by Maxar Satellite Imagery"© 2020. doi:10.5258/SOTON/WP00677- Bondarenko M., Nieves J. J., Stevens F. R., Gaughan A. E., Tatem A. and Sorichetta A. 2020. wpgpRFPMS: Random Forests population modelling R scripts, version 0.1.0. University of Southampton: Southampton, UK. https://dx.doi.org/10.5258/SOTON/WP00665- Ecopia.AI and Maxar Technologies. 2020. Digitize Africa data. http://digitizeafrica. The units are number of people per pixel. The mapping approach is Random Forest. "NoData" values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020). The mapping approach is the Random Forestsai "NoData" values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020). The mapping approach is the Random Forestsai The dataset is available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc (approximately 1k The units are number of people per pixel. The mapping approach is Random Forest. The dataset is available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc (approximately 1k The mapping approach is Random Forest-based dasymetric redistribution.

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