This article was accepted into the corpus but its outbound wikilinks were never NER-processed — typical at the deepest BFS hop or when the run's entity cap was reached. No expansion funnel to show.
| Gridded Population of the World | |
|---|---|
| Name | Gridded Population Dataset |
| Producer | Center for International Earth Science Information Network (CIESIN), NASA Socioeconomic Data and Applications Center, Columbia University |
| First release | 1995 |
| Latest release | 2018 |
| Format | Raster, GeoTIFF, NetCDF |
| Resolution | 30 arc-seconds to 1 km |
| License | Various academic and public domain policies |
Gridded Population of the World is a global raster dataset that distributes population counts into uniform spatial cells to enable spatial analysis across United Nations, World Bank, United States Agency for International Development, European Commission and academic projects. The dataset supports work by agencies such as United Nations Development Programme, World Health Organization, International Monetary Fund, Food and Agriculture Organization and research at institutions like Massachusetts Institute of Technology, Harvard University and Stanford University.
The dataset represents population totals and densities as gridded surfaces for countries and subnational regions widely used by United Nations Population Division, WorldPop, CIESIN researchers, NASA projects and nongovernmental organizations including Médecins Sans Frontières and International Committee of the Red Cross. It provides multi-temporal layers aligning with censuses from national statistical offices such as United States Census Bureau, Office for National Statistics (UK), Instituto Nacional de Estadística (Spain) and Statistics Canada to support analyses by European Space Agency, National Aeronautics and Space Administration and universities including University of Oxford.
Population counts are redistributed from administrative units reported by agencies like UNESCO, International Organization for Migration, Organisation for Economic Co-operation and Development and national bureaus into grid cells using ancillary datasets such as land cover products from MODIS, settlement maps from Landsat and nighttime lights from NOAA National Centers for Environmental Information. Dasymetric techniques and areal weighting leverage inputs from Global Land Cover Facility, SRTM, ASTER and infrastructure layers produced by OpenStreetMap contributors to refine allocation. Statistical modeling draws on demographic controls from Demographic and Health Surveys, Pew Research Center analyses and census microdata shared under agreements with institutions like IPUMS.
Releases are versioned and cited by year with major iterations in 1995, 2000, 2005, 2010 and 2015/2018 that correspond to updated inputs from UN World Population Prospects, Global Administrative Areas (GADM), FAO and newer remote-sensing sources including Sentinel satellites. Outputs include population count grids, population density grids, urban extent masks and population by age/sex where available for use in platforms such as ArcGIS, QGIS, GRASS GIS and programming environments like R (programming language), Python (programming language) and MATLAB.
Gridded population products inform humanitarian response by United Nations Office for the Coordination of Humanitarian Affairs, epidemic modeling by Centers for Disease Control and Prevention, World Health Organization and vaccine distribution planning coordinated with Gavi, the Vaccine Alliance. Urban planners at municipal governments and firms like McKinsey & Company employ grids for transport modeling, energy access planning with International Energy Agency guidance, and climate risk assessment in collaboration with research centers such as Intergovernmental Panel on Climate Change teams. Conservation organizations including World Wildlife Fund use population overlays with biodiversity maps from IUCN and Convention on Biological Diversity assessments.
Accuracy depends on the quality of source censuses from national statistical offices and on spatial proxies from satellite missions such as Landsat, MODIS and VIIRS. Limitations include temporal mismatches with surveys from Demographic and Health Surveys and uncertainty in areas with informal settlements referenced by Human Rights Watch reports or conflict-affected regions documented by Amnesty International. Errors arise from administrative boundary inconsistencies with datasets like GADM and from modeling assumptions compared against ground-truthing by institutions such as WorldPop and national mapping agencies like Ordnance Survey.
Data are distributed through repositories operated by CIESIN, NASA's Socioeconomic Data and Applications Center and academic mirrors, and are accessed by researchers at University of California, Berkeley, ETH Zurich and Australian National University. Licensing varies by product and year, often permitting academic and noncommercial use under institutional policies similar to datasets from Global Administrative Unit Layers and Humanitarian Data Exchange; commercial use may require separate agreements with data custodians and contributors including national statistical institutes such as Instituto Brasileiro de Geografia e Estatística.
Originating in the mid-1990s with efforts led by CIESIN and collaborators at Columbia University, the project drew on earlier cartographic population efforts linked to United Nations demographic programs and remote-sensing advances from NASA and USGS. Subsequent collaborations involved international partners such as World Bank research teams, European Commission Joint Research Centre, and mapping initiatives like OpenStreetMap and Global Human Settlement Layer to incorporate higher-resolution inputs and to align with global assessments from Millennium Development Goals and later Sustainable Development Goals monitoring by United Nations Statistical Commission.
Category:Population datasets