Gridded population estimates for Ukraine using UN COD-PS estimates 2020, version 2.0

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 WorldPop at the University of Southampton. These data include gridded estimates of population at approximately 100m and 1km for 2022, along with estimates of the number of people belonging to individual age-gender groups. These results were produced using subnational population estimates for Sudan in 2022 provided in the Common Operational Dataset on Population Statistics (COD-PS) and built-up surfaces/volumes covariates extracted from GHSL datasets; GHS-BUILT-Surface epoch 2020 layer , combined with Digitize Africa building footprints, were used to delineate settled areas. The constrained and unconstrained top-down disaggregation method was used to produce the datasets, i.e. population was only estimated within areas classified as containing built settlement. The modelling work and geospatial data processing was led by Bondarenko M. and Leasure D.R.. Oversight was provided by Tatem A.J. For further details, please, read the Release Statement. **Recommended citations** Bondarenko M., Leasure D.R., and Tatem A.J. 2023 *Gridded population estimates for Sudan using UN COD-PS estimates 2022, version 2.0. WorldPop, University of Southampton.* doi:10.5258/SOTON/WP00761 **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. 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.

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network CIESIN in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work, as well as Christopher Lloyd, particularly for the processing of residential/non-residential building footprints. In-country engagements were done by Benard Mitto, Justine Dowden (CIESIN) and Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and gender and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem. For further details, please, read the Release Statement. **Release content** 1. KEN_population_v1_0_gridded.tif 2. KEN_population_v1_0_agesex.zip 3. KEN_population_v1_0_mastergrid.tif **Recommended citations** Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022. *Census disaggregated gridded population estimates for Kenya (2021), version 1.0* University of Southampton. doi:10.5258/SOTON/WP00747 **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 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.

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