Gridded Population Estimates for Yemen using UN COD-PS Estimates 2019, 2023 and 2024, version 1.0
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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.
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