Gridded population estimates for Sudan using UN COD-PS estimates 2022, version 2.0

These data were produced by WorldPop at the University of Southampton and World Bank Group . These data include gridded estimates of population at approximately 100m for 2019, 2023 and 2024 along with estimates of the number of people belonging to individual age-gender groups. These results were produced using subnational population estimates for Yemen provided in the Common Operational Dataset on Population Statistics (2019, 2023 COD-PS and 2024 COD-PS ) and Subnational Administrative Boundaries for Yemen provided by OCHA. For further details, please, read the Release Statement. **Recommended citations** WorldPop and World Bank Group. 2024 *Gridded population estimates for Yemen using UN COD-PS estimates 2019, 2023 and 2024, version 1.0*. https://data.worldpop.org/repo/prj/WP_WB/YEM/v1/ **License** *These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release@worldpop.org for more information.* The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release@worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.

These data were produced by WorldPop at the University of Southampton and the ‘Smart Cities and Spatial Development’ team at the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR). These data include gridded estimates of population at approximately 100m and 1km resolution for 2020, along with estimates of the number of people belonging to individual age-gender groups. These results were produced using subnational population estimates for Ukraine in 2020 provided in the Common Operational Dataset on Population Statistics (COD-PS) and building height/area/fraction/volume covariates extracted from the World Settlement Footprint (WSF) imperviousness and WSF-3D by DLR. The constrained top-down disaggregation method was used to produce the datasets. The modelling work and geospatial data processing was led by Bondarenko M., Palacios-Lopez D., Sorichetta A., Leasure D.R., ,Zeidler J., Marconcini M., and Esch T.. Oversight was provided by Tatem A.J. Internal WorldPop peer reviews that helped to improve the results and documentation was provided by Lazar A.N.. **Main data sources** - The German Aerospace Centre’s (DLR) WSF imperviousness and WSF 3D products (WSF-3D). - Subnational population estimates for Ukraine in 2020 provided in the Common Operational Dataset on Population Statistics (COD-PS). The subnational population estimates were produced using baseline information from the 2001 Population Census of Ukraine and annual birth and death registration data since then. - Subnational Administrative Boundaries for Ukraine provided by OCHA . - Geospatial covariate layers available at WorldPop. For further details, please, read the Release Statement. **Release content** 1. ukr_pop_2020_100m_constrained_v2.zip 2. ukr_pop_2020_1km_constrained_v2.zip 3. ukr_agegender_2020_100m_constrained_v2.zip 4. ukr_agegender_2020_1km_constrained_v2.zip 5. ukr_agegender_0_18_2020_100m_constrained_v2.zip 6. ukr_agegender_0_18_2020_1km_constrained_v2.zip **Recommended citations** Bondarenko M., Palacios-Lopez D., Sorichetta A., Leasure D.R., Zeidler J., Marconcini, M., Esch T., and Tatem A.J. 2022 *Gridded population estimates for Ukraine using UN COD-PS estimates 2020, version 2.0*. WorldPop and DLR, University of Southampton. doi:10.5258/SOTON/WP00735 **License** *These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information*. The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.

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These data were produced by the WorldPop Research Group at the University of Southampton. These data include gridded estimates of population at approximately 100m and 1km resolution for 2020, along with estimates of the number of people belonging to individual age-gender groups. These results were produced using Subnational Population Statistics 2020 for Ukraine provided in the Common Operational Dataset on Population Statistics (COD-PS) and ORNL LandScan HD for Ukraine 2022 settlement layer. The datasets are produced using the "top-down" method, with both the unconstrained and constrained top-down disaggregation methods used to produce two different datasets. The differences between constrained and un-constrained methods are described here . **Main data sources** - Subnational Population Statistics for Ukraine provided by Common Operational Dataset on Population Statistics (COD-PS). The subnational population statistics were estimated using baseline information from the 2001 Population Census of Ukraine and annual birth and death registration data since the last census. - Settlement layer ORNL LandScan HD for Ukraine. - Subnational Administrative Boundaries for Ukraine provided by OCHA. - Geospatial covariate layers available at WorldPop. For further details, please, read the Release Statement. **Release content** 1. ukr_pop_2020_100m_unconstrained_v1_0.zip 2. ukr_pop_2020_100m_constrained_v1_0.zip 3. ukr_pop_2020_1km_unconstrained_v1_0.zip 4. ukr_pop_2020_1km_constrained_v1_0.zip 5. ukr_agegender_2020_100m_unconstrained_v1_0.zip 6. ukr_agegender_2020_100m_constrained_v1_0.zip 7. ukr_agegender_2020_1km_unconstrained_v1_0.zip 8. ukr_agegender_2020_1km_constrained_v1_0.zip 9. ukr_agegender_0_18_2020_1km_unconstrained_v1_0.zip 10. ukr_agegender_0_18_2020_1km_constrained_v1_0.zip **Recommended citations** Bondarenko M., Sorichetta A., Leasure DR. and Tatem AJ. 2022 *Gridded population estimates for Ukraine using UN COD-PS estimates 2020, version 1.0*. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00734 **License** *These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information*. The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.

These data were produced by the WorldPop Research Group at the University of Southampton. This work was funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom's Department for International Development (OPP1182408). The primary intended use of these data was aiding the BMGF field teams. The modelling work was led by Claire Dooley with support from Chris Jochem and oversight by WorldPop director Andy Tatem and GRID3 lead Attila Lazar. The support of the whole WorldPop group is acknowledged, as well as the our GRID3 partners (UNFPA, Columbia University and Flowminder). We thank the teams at IOM and ACLED for their excellent work in collecting data and making it freely available. This work was supported with funding from the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (DFID). These data may be distributed using a Creative Commons Attribution Share-Alike 4.0 License. __DATA DESCRIPTION__ This dataset provides population estimates for each settled 100m grid square in South Sudan. The grid square values were derived using the National Bureau of Statistics’ 2019 population projection estimates that were adjusted to account for displacement of people. The locations people have been displaced to were directly obtained from IOM’s Displacement Tracking Matrix (DTM). The locations people have been displaced from were derived using DTM and the Armed Conflict Locations and Events Database (ACLED). Numbers of displaced people per location were calculated using recorded numbers of international refugees and internally displaced persons. For further details, please, read SSD_population_v1_0_README.pdf __Recommended citation__ _WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. South Sudan 2019 gridded population estimates from census projections adjusted for displacement, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00659_

These data were produced by WorldPop at the University of Southampton. These data include gridded estimates of population at approximately 100m for 2021, along with estimates of the number of people belonging to individual age-gender groups. These results were produced using subnational population estimates for Turkey in 2021 provided in the Common Operational Dataset on Population Statistics (COD-PS) and built-up surfaces/volumes/height covariates extracted from GHSL datasets. The constrained and unconstrained top-down disaggregation method was used to produce the datasets. The modelling work and geospatial data processing was led by Bondarenko M., Priyatikanto R., Sorichetta A. Oversight was provided by Tatem A.J. For further details, please, read the Release Statement. **Recommended citations** Bondarenko M., Priyatikanto R., Sorichetta A., and Tatem A.J.. 2023 *Gridded population estimates for Turkey using UN COD-PS estimates 2021, version 1.0*. WorldPop University of Southampton. doi:10.5258/SOTON/WP00758 **License** *These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release@worldpop.org for more information.* The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release@worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.