Frequently Asked Questions (FAQ)

This work is licensed under the Creative Commons Attribution 4.0 International License ( Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided.

WorldPop gridded datasets are provided in geotiff format. This data format is readable by all Geographical Information System software types, including ArcGIS, QGIS, MapInfo, SagaGIS and many others.

To learn how WorldPop converts census data into gridded estimates, please see our methods pagecase study pages and publications page

WorldPop integrate many different types of geospatial data in building demographic datasets. please see our methods pagecase study pages and publications page for more details.

Different coordinate reference systems (CRS) are employed for different countries, and for different types of data. Country-level datasets presenting ‘People per hectare’ (pph) values are mapped in a suitable country-level map projection, typically UTM (Universal Transverse Mercator) or occasionally a specific country grid. Datasets presenting ‘People per pixel’ (ppp) values are not projected; they are mapped to a global geographic coordinate system, GCS_WGS_84.

Yes, detailed descriptions of the methods and improvements made in the WorldPop data collection are described in the papers found on the publications page.

WorldPop datasets have been developed incrementally over the past 5 years on a country-by-country basis. Consequently some variation in methods and presentation persists in regions that have not been recently mapped. However we are currently undergoing a process of standardisation across all aspects of the project, data products and methodologies.

The WorldPop Project will shortly be releasing an open access archive (alpha version) of harmonised 100 m gridded geospatial data layers derived from a variety of sources. The archive will provide a range of metrics relevant to global human population mapping at fine spatial scales. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include airports, highways, landcover, nightlights, precipitation, rail network, travel time to major cities, and waterways. The archive can be downloaded from the WorldPop Project website. An expanded archive (beta version) is currently in development. Additionally, global age-structured population datasets for the 2000-2020 period are under production, together with estimates of births and pregnancies. Expansion of the existing internal migration datasets to incorporate international flows is also under development.

WorldPop datasets are updated when new census or geospatial datasets are available, or for specific stakeholder needs. The date of production of each dataset is provided on the dataset download page and the source and date of input datasets are provided in metadata files and on the methods page.

WorldPop datasets have been downloaded and used by researchers and policy makers based in governments of every low income and lower-middle income country in Africa, Asia and the Americas, supporting development, health and planning. Moreover, WorldPop data are used by many international agencies, including the International Red Cross, Bill and Melinda Gates Foundation, FAO, UNDP, UNFPA, UNOCHA, CDC, China CDC, WFP, WWF, MSF, IOM, PMI, iMMAP, NASA, Population Council, Clinton Health Access Initiative, DFID, USGS, USAID and IDMC. See the ‘who uses our data’ section on the main homepage as well as the case studiesabout worldpop, and publications page for further details.

The United Nations produce their own estimates of national population totals that take into account a range of factors. These estimates can sometimes differ from the totals obtained in national censuses and used by governments. We therefore produce two versions of our population datasets: (i) adjusted nationally to match census totals and (ii) adjusted nationally to match UN estimates. This provides flexibility to users to choose which numbers are most appropriate for their analyses.

Regarding how to map the data, for each country of interest, I would suggest to use the ArcGIS “XY To Line” tool after adding a “GEONAMEID” field to the corresponding migration csv table available here:

The “GEONAMEID” field can then be used to join the “PrdMIG” information to the attribute table of the corresponding flowline dataset produced using the “XY To Line” tool – additional hints on how to create flow maps with ArcGIS can be found here:

For all datasets, please cite the WorldPop website as the source:
Additionally, the following academic publications should be cited for the specific datasets listed:

*Americas population data: Alessandro Sorichetta, Graeme M. Hornby, Forrest R. Stevens, Andrea E. Gaughan, Catherine Linard, Andrew J. Tatem, 2015, High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020, Scientific Data, doi:10.1038/sdata.2015.45

*Africa population count data: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

*Africa age-structure data: Tatem, Andrew J., Garcia, Andres J., Snow, Robert W., Noor, Abdisalan M., Gaughan, Andrea E.,Gilbert, Marius and Linard, Catherine, 2013, Millennium development health metrics: where do Africa’s children and women of childbearing age live? Population Health Metrics, 11, (1), 11.

*Asia population count data: Gaughan AE, Stevens FR, Linard C, Jia P and Tatem AJ, 2013, High resolution population distribution maps for Southeast Asia in 2010 and 2015, PLoS ONE, 8(2): e55882.

*Births and pregnancies data: Tatem AJ, Campbell J, Guerra-Arias M, de Bernis L, Moran A, Matthews Z, 2014, Mapping for maternal and newborn health: the distributions of women of childbearing age, pregnancies and births, International Journal of Health Geographics, 13:2

*Urban change data: A Schneider, C M Mertes, A J Tatem, B Tan, D Sulla-Menashe, S J Graves, N N Patel, J A Horton, A E Gaughan, J T Rollo, I H Schelly, F R Stevens and A Dastur, 2015, A new urban landscape in East-Southeast Asia, 2000-2010, Environmental Research Letters, 10 034002

*Internal migration data: Alessandro Sorichetta, Tom J. Bird, Nick W. Ruktanonchai, Elisabeth zu Erbach-Schoenberg, Carla Pezzulo, Natalia Tejedor, Ian C. Waldock, Jason D. Sadler, Andres J. Garcia, Luigi Sedda & Andrew J. Tatem. Mapping internal connectivity through human migration in malaria endemic countries Scientific Data 3, Article number: 160066 (2016). doi:10.1038/sdata.2016.66

*Poverty data: Tatem AJ, Gething PW, Pezzulo C, Weiss D and Bhatt S, 2014, Development of High-Resolution Gridded Poverty Surfaces, Report for the Bill and Melinda Gates Foundation:

*Dynamic population data: Deville, P., Linard, C., Martin, S., Gilbert, M., Stevens, F.R., Gaughan, A.E., Blondel, V.D. and Tatem, A.J., 2014, Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences (doi:10.1073/pnas.1408439111).

*Global air passenger data: Liang Mao, Xiao Wu, Zhuojie Huang, Andrew J. Tatem, 2015, Modeling monthly flows of global air travel passengers: An open-access data resource, Journal of Transport Geography, 56:60, doi:10.1016/j.jtrangeo.2015.08.017