Estimated total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel with country totals adjusted to match the corresponding official United Nations population estimates that have been prepared by the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat (2019 Revision of World Population Prospects). "NoData" values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020.The mapping approach is the Random Forests-based dasymetric redistribution developed by Stevens et al. (2015). The disaggregation was done by Maksym Bondarenko (WorldPop) and David Kerr (WorldPop), using the Random Forests population modelling R scripts (Bondarenko et al., 2020), with oversight from Alessandro Sorichetta (WorldPop).SOURCE DATA:This dataset was produced based on the 2020 population census/projection-based estimates for 2020 (information and sources of the input population data can be found here).Built-Settlement Growth Model (BSGM) outputs produced by Jeremiah J.Nieves et al. 2020.Geospatial covariates representing factors related to population distribution, were obtained from the "Global High Resolution Population Denominators Project" (OPP1134076).REFERENCES:- Stevens FR, Gaughan AE, Linard C, Tatem AJ (2015) Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data. PLoS ONE 10(2): e0107042. https://doi.org/10.1371/journal.pone.0107042- 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).- Jeremiah J. Nieves, Alessandro Sorichetta, Catherine Linard, Maksym Bondarenko, Jessica E. Steele, Forrest R. Stevens, Andrea E. Gaughan, Alessandra Carioli, Donna J. Clarke, Thomas Esch, Andrew J. Tatem, Annually modelling built-settlements between remotely-sensed observations using relative changes in subnational populations and lights at night, Computers, Environment and Urban Systems,Volume 80,2020,101444,ISSN 0198-9715,https://doi.org/10.1016/j.compenvurbsys.2019.101444- Nieves, J.J.; Bondarenko, M.; Sorichetta, A.; Steele, J.E.; Kerr, D.; Carioli, A.; Stevens, F.R.; Gaughan, A.E.; Tatem, A.J. Predicting Near-Future Built-Settlement Expansion Using Relative Changes in Small Area Populations. Remote Sens. 2020, 12, 1545.- Bondarenko M., Nieves J. J., Stevens F. R., Gaughan A. E., Tatem A. and Sorichetta A. 2020. wpgpRFPMS: Random Forests population modelling R scripts, version 0.1.0. University of Southampton: Southampton, UK. https://dx.doi.org/10.5258/SOTON/WP00665

DATASET: Version 4.0 2010 estimates of numbers of people per grid square for 2010, 2015, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/), and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: 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. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: WorldPop naming convention applied; example SSD_ppp_2010_adj_v4.tif = South Sudan population per pixel (ppp) map for 2010 adjusted to match UN national estimates (adj), dataset version 4 (v4). DATE OF PRODUCTION: Jan 2013 (Updated July 2018) CITATION: WorldPop. 2013. South Sudan 100m Population, Version 4. University of Southampton. DOI: 10.5258/SOTON/WP00642.

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 Bill and Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office (INV-009579, formerly OPP1182425), and GRID3 COVID-19 Support Scale-up (INV-018067). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network in the Columbia Climate School at Columbia University, and the Flowminder Foundation. The new age-structured population estimates are based on the existing Census-based gridded population estimates for Burkina Faso (2019), version 1.0 (WorldPop and Institut National de la Statistique et de la Demographie du Burkina Faso, 2020). Duygu Cihan, Heather Chamberlain and Thomas Abbott led the data processing, with advice from Édith Darin.RELEASE CONTENT Aggregated_BFA_under18_population_100m.tif Aggregated_BFA_18_45_population_100m.tif Aggregated_BFA_over45_population_100m.tifFILE DESCRIPTIONS The coordinate system for all GIS files is the geographic coordinate system WGS84 (World Geodetic System 1984, EPSG: 4326). Aggregated_BFA_ under18_population _100m.tifThis geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population of persons aged under 18 (0-17) per grid cell across Burkina Faso. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.Aggregated_BFA_18_45_population_100m.tif This geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population of persons aged 18 to 45 (18-45) per grid cell across Burkina Faso. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas. Aggregated_BFA_over45_population_100m.tif This geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population of persons aged over 45 (46+) per grid cell across Burkina Faso. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.METHODS OVERVIEW Processing: The existing 2019 gridded population estimates (WorldPop and Institut National de la Statistique et de la Demographie du Burkina Faso, 2020) include age- and sex- structured population estimates for 5 year age classes, based on the age and sex breakdown of population totals at the national level, from the preliminary census results. A Sprague multiplier approach was used to further disaggregate the 5-year age classes at the national level, to create three custom age-classes (under 18, 18-45 and over 45). The population for each of these custom age classes, was calculated as the proportion of the total population at the national level. This proportion was applied to the count of total population at the grid cell level.ASSUMPTIONS AND LIMITATIONS The custom age classes are estimated using a Sprague multiplier approach to interpolate the 5-year age classes and provide the population for a single year age class, which is then summed to provide the custom age classes. Interpolation introduces uncertainty in the estimates.The population estimates for the custom age classes were calculated from national level totals for 5-year age classes. A constant age-structure across all grid cells was assumed in applying the national proportions for the custom age classes to the grid cell level.RELEASE HISTORYVersion 1.0 (25/05/2022) - Original release of this data set.WORKS CITEDDooley, C. A. and Tatem, A.J. 2020. Gridded maps of building patterns throughout sub-Saharan Africa, version 1.0. University of Southampton: Southampton, UK. Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. https://dx.doi.org/10.5258/SOTON/WP00666.WorldPop and Institut National de la Statistique et de la Demographie du Burkina Faso. 2020. Census-based gridded population estimates for Burkina Faso (2019), version 1.0. WorldPop, University of Southampton. https://dx.doi.org/10.5258/SOTON/WP00687

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

Estimated total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. "NoData" values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020.The mapping approach is the Random Forests-based dasymetric redistribution developed by Stevens et al. (2015). The disaggregation was done by Maksym Bondarenko (WorldPop) and David Kerr (WorldPop), using the Random Forests population modelling R scripts (Bondarenko et al., 2020), with oversight from Alessandro Sorichetta (WorldPop).SOURCE DATA:This dataset was produced based on the 2020 population census/projection-based estimates for 2020 (information and sources of the input population data can be found here).Built-Settlement Growth Model (BSGM) outputs produced by Jeremiah J.Nieves et al. 2020.Geospatial covariates representing factors related to population distribution, were obtained from the "Global High Resolution Population Denominators Project" (OPP1134076).REFERENCES:- Stevens FR, Gaughan AE, Linard C, Tatem AJ (2015) Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data. PLoS ONE 10(2): e0107042. https://doi.org/10.1371/journal.pone.0107042- 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).- Jeremiah J. Nieves, Alessandro Sorichetta, Catherine Linard, Maksym Bondarenko, Jessica E. Steele, Forrest R. Stevens, Andrea E. Gaughan, Alessandra Carioli, Donna J. Clarke, Thomas Esch, Andrew J. Tatem, Annually modelling built-settlements between remotely-sensed observations using relative changes in subnational populations and lights at night, Computers, Environment and Urban Systems,Volume 80,2020,101444,ISSN 0198-9715,https://doi.org/10.1016/j.compenvurbsys.2019.101444- Nieves, J.J.; Bondarenko, M.; Sorichetta, A.; Steele, J.E.; Kerr, D.; Carioli, A.; Stevens, F.R.; Gaughan, A.E.; Tatem, A.J. Predicting Near-Future Built-Settlement Expansion Using Relative Changes in Small Area Populations. Remote Sens. 2020, 12, 1545.- Bondarenko M., Nieves J. J., Stevens F. R., Gaughan A. E., Tatem A. and Sorichetta A. 2020. wpgpRFPMS: Random Forests population modelling R scripts, version 0.1.0. University of Southampton: Southampton, UK. https://dx.doi.org/10.5258/SOTON/WP00665

These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF)

The CPC-ONS-UUK Survey of Graduating International Students (SoGIS) is a collaborative project between the ESRC Centre for Population Change (CPC) at the University of Southampton, the Office for National Statistics (ONS) and Universities UK (UUK). SoGIS wave 1 collected detailed information from international students in UK Higher Education in their final year of study. SoGIS wave 2 is a follow-up survey administered to a subsample of students who participated in wave 1. The survey sampled both undergraduate and postgraduate, EU and non-EU finalist students. SoGIS Wave 1 contains 3560 responses from a sample of 101,049 (response rate 3.5%). SoGIS Wave 2 contains 563 responses from a sample of 1,517 (37% response rate). SoGIS provides valuable information about the post-study intentions, certainty of these intentions, travel patterns, use of public services, and working patterns whilst studying of international students approaching course completion. The survey increases our understanding of students migratory and employment intentions after studying.

Funded by the Economic and Social Research Council, the ESRC Centre for Population Change (CPC) is investigating how and why our population is changing and what this means for people, communities and governments. The Centre is a joint partnership between the Universities of Southampton, St. Andrews, and Stirling. Our research agenda is planned in collaboration with the Office for National Statistics and the National Records of Scotland. CPC is a founding partner of Population Europe, the network of Europe's leading research centres in the field of policy-relevant population studies.

The pattern of our lives is continuously changing; many of us now remain in education for longer than in the past, we delay becoming parents and we are living longer than ever before. The households we live in are more complex with more step- and half-kin but also more of us live alone at some point in our lives. Many of us move around locally, nationally and internationally for work and family. Our behaviours interact to create the society in which we live. CPC research aims to understand the causes and consequences of changes in births, deaths, relationships and migration to enable policy makers and planners to know how, when and where to respond. By finding out how our population is changing we can improve the world in which we live.

CPC research is organised around five thematic areas: 1. Fertility and family change 2. Increasing longevity and the changing life course 3. New mobilities and migration 4. Understanding intergenerational relations and exchange 5. Integrated demographic estimation and forecasting

These thematic areas explicitly recognise the dynamic interaction of the individual components of population change both with each other and with economic and social processes.