WorldPop Humanitarian Data | 1082 Datasets

Burundi - Age and Sex Structures

WorldPop

Time Period of the Dataset [?]: January 01, 2019-December 31, 2019 ... More

This dataset updates: Never

Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map population age and sex counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets. 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).

GeoTIFF

Gridded Population Estimates for Ukraine using UN COD-PS Estimates 2020 (version 1.0)

WorldPop

400+ Downloads

Time Period of the Dataset [?]: March 21, 2022-March 21, 2022 ... More

This dataset updates: Never

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-sex 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 ukr_pop_2020_100m_unconstrained_v1_0.zip ukr_pop_2020_100m_constrained_v1_0.zip ukr_pop_2020_1km_unconstrained_v1_0.zip ukr_pop_2020_1km_constrained_v1_0.zip ukr_agesex_2020_100m_unconstrained_v1_0.zip ukr_agesex_2020_100m_constrained_v1_0.zip ukr_agesex_2020_1km_unconstrained_v1_0.zip ukr_agesex_2020_1km_constrained_v1_0.zip ukr_agesex_0_18_2020_1km_unconstrained_v1_0.zip ukr_agesex_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.

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GeoTIFF

Gridded Disaggregated Population Estimates for Kenya (version 1.0)

WorldPop

90+ Downloads

Time Period of the Dataset [?]: July 22, 2022-July 22, 2022 ... More

This dataset updates: Never

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 sex 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 KEN_population_v1_0_gridded.tif KEN_population_v1_0_agesex.zip 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.

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GeoTIFF

Gridded Population Estimates for Yemen using UN COD-PS Estimates 2019, 2023...

WorldPop

100+ Downloads

Time Period of the Dataset [?]: July 01, 2024-March 26, 2025 ... More

This dataset updates: Never

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-sex 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.

GeoTIFF
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Bottom-up gridded population estimates for Nigeria, version 2.1

WorldPop

60+ Downloads

Time Period of the Dataset [?]: August 22, 2023-March 26, 2025 ... More

This dataset updates: Never

This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to various age-sex groups. Version 2.1 is an update to the previous version 2.0 gridded population estimates and is based on a correction of the settlement map. These model-based population estimates most likely represent the time period around 2019, corresponding to the period when the satellite imagery was processed to generate building footprints. Populations are mapped only into areas where residential settlements are predicted. These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 Bridge Funding project with funding from the Bill and Melinda Gates Foundation (INV-045694). Project partners included the GRID3 Inc and the Center for International Earth Science Information Network in the Earth Institute at Columbia University. Statistical modelling was originally led by Chris Jochem and Doug Leasure with additional support and oversight from Attila Lazar and Andy Tatem. Ortis Yankey led the population map update with additional support from Edith Darin. 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. SUGGESTED CITATIONS WorldPop. 2023. Bottom-up gridded population estimates for Nigeria, version 2.1. WorldPop, University of Southampton. DOI: 10.5258/SOTON/WP00765

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GeoTIFF

Modelled Population Estimates for Papua New Guinea, version 1.0

WorldPop

100+ Downloads

Time Period of the Dataset [?]: January 01, 2020-December 01, 2021 ... More

This dataset updates: Never

This project was initiated in 2021 to generate modelled population estimates for Papua New Guinea (PNG) to support their census preparations. It was powered by the Australian Government through the PNGAus partnership, the United Nations Population Fund (UNFPA ) and the PNG National Statistical Office. The project team combined recent 2019-2021 malaria bednet campaign data, urban structural listing 2021 data, and geospatial covariates to model and estimate population numbers at census unit level, and aggregate at other relevant administrative units (e.g., national, province, and districts) using a Bayesian statistical hierarchical modelling framework. The approach facilitated simultaneous accounting for the multiple levels of variability within the data hierarchy. It also allowed the quantification of uncertainties in parameter estimates. These model-based population estimates can be considered as most accurately representing the years 2020-21. This time period corresponds to the malaria survey and urban structural listing survey observations (2019-2021; median year: 2020) and the period of the satellite imagery used to generate settlement footprints (2021). Although the methods were robust enough to explicitly account for key random biases within the datasets, it is noted that systematic biases, which may arise from sources other than random errors within the observed data collection process, are most likely to remain. These data were produced by the WorldPop Research Group at the University of Southampton in collaboration with the National Statistical Office of PNG and UNFPA under the project called “Population-modelled estimation for Papua New Guinea in collaboration with the National Statistical Office, 2021-22” (PNG40-0000004504). The final statistical modelling was designed, developed, and implemented by Chris Nnanatu. Data processing was done by Amy Bonnie with additional support from Tom Abbott, Tom McKeen, Heather Chamberlain, Ortis Yankey, Duygu Cihan and Assane Gadiaga. Project oversight was done by Attila Lazar and Andy Tatem. Household survey listing data were provided by the National Statistical Office, and the settlement footprint was generated by Planet. Please, note that the same modelled population data (with minor rounding difference of 41 in the national total) can also be downloaded from the NSO’s website: https://www.nso.gov.pg/statistics/population/ How to cite this work WorldPop and National Statistical Office of Papua New Guinea. 2022. Census-independent population estimates for Papua New Guinea (2020-21), version 1.0. WorldPop, University of Southampton. DOI: 10.5258/SOTON/WP00763.

Gridded disaggregated population estimates for Kenya , version 2.0

WorldPop

100+ Downloads

Time Period of the Dataset [?]: July 11, 2023-March 26, 2025 ... More

This dataset updates: Never

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 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. In-country engagements were done by David Kyalo, Olena Borkovska ( GRID3 , 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 sex 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. Recommended citations Gadiaga A. N., Abbott T. J., Chamberlain H., Lazar A. N., Darin E., Tatem A. J. 2023. Census disaggregated gridded population estimates for Kenya (2022), version 2.0. University of Southampton. doi:10.5258/SOTON/WP00762 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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GeoTIFF

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

WorldPop

50+ Downloads

Time Period of the Dataset [?]: May 08, 2023-March 26, 2025 ... More

This dataset updates: Never

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-sex 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.

Gridded population estimates for Turkey using UN COD-PS estimates 2021, version 1.0

WorldPop

90+ Downloads

Time Period of the Dataset [?]: January 01, 2021-December 31, 2021 ... More

This dataset updates: Never

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-sex 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.

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GeoTIFF

Census-cartography-based gridded population estimates for Mali (2020), version 1.0

WorldPop

50+ Downloads

Time Period of the Dataset [?]: December 30, 2022-March 26, 2025 ... More

This dataset updates: Never

These data consist of modelled gridded population estimates produced at a spatial resolution of approximately 100m across Mali. The estimates comprise a combination of total population counts at enumeration area level collected by the census cartography team of the Mali Statistics Office and modelled population counts created using a Bayesian statistical model for areas that could not be covered by the cartography team because of security issues. The main input data for the model are the cartography data collected in the safe part of the country in 2019-2020 (628 out of 714 Communes –administrative level 3–, that is 87% of the country territory). Other essential input data include metrics derived from building footprints, which were automatically delineated by Ecopia.AI in 2021 using satellite imagery collected by Maxar Technologies between 2010 and 2021. The modelled population estimates represent the period of the census cartography, but their consistency may be impacted by the accuracy of the building footprints. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 Project, 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 (INV 009579, formerly OPP 1182425). The study was approved by the Faculty Ethics Committee of the University of Southampton (ERGO II 64957). The project was led by the Center for International Earth Science Information Network (CIESIN) at Columbia University, in collaboration with the WorldPop Research Group at the University of Southampton, the United Nations Fund for Population (UNFPA) and the Malian Institut National de la Statistique (INSTAT). The production of these data was led by Edith Darin (WorldPop) with support from Matthias Kuépié and Jean Wakam (UNFPA), Abdoul Karim Diawara, Assa Gakou and Siaka Cissé (Institut National de la Statistique), and Attila N Lazar (WorldPop) and Andrew J Tatem (WorldPop). The authors acknowledge the support of their respective institutions in the completion of this work. Recommended citations WorldPop and Institut National de la Statistique du Mali. 2022. Census-cartography-based gridded population estimates for Mali (2020), version 1.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00745 License These data may be redistributed following the terms of a Creative Commons Share-Alike Attribution 4.0 International (CC BY SA 4.0) license

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

WorldPop

300+ Downloads

Time Period of the Dataset [?]: March 28, 2022-March 26, 2025 ... More

This dataset updates: Never

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-sex 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 ukr_pop_2020_100m_constrained_v2.zip ukr_pop_2020_1km_constrained_v2.zip ukr_agesex_2020_100m_constrained_v2.zip ukr_agesex_2020_1km_constrained_v2.zip ukr_agesex_0_18_2020_100m_constrained_v2.zip ukr_agesex_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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GeoTIFF

Guyana - Age and sex structures

WorldPop

Time Period of the Dataset [?]: January 01, 2019-December 31, 2019 ... More

This dataset updates: Never

Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map population age and sex counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets. 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).

GeoTIFF

Netherlands (Kingdom of the) - Age and Sex Structures

WorldPop

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00646

GeoTIFF

Türkiye - Age and Sex Structures

WorldPop

100+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00646

GeoTIFF

Eswatini - Population Density

WorldPop

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Netherlands (Kingdom of the) - Population Density

WorldPop

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

North Macedonia - Population Density

WorldPop

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Türkiye - Population Density

WorldPop

50+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Zimbabwe - Population Density

WorldPop

200+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Zambia - Population Density

WorldPop

100+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

South Africa - Population Density

WorldPop

500+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Yemen - Population Density

WorldPop

500+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Samoa - Population Density

WorldPop

40+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Wallis and Futuna Islands - Population Density

WorldPop

10+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF

Vanuatu - Population Density

WorldPop

60+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: Never

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. 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). https://dx.doi.org/10.5258/SOTON/WP00674

GeoTIFF