Note: "Gridded Population of the World, v4" is now available and supersedes GPWv3. GPWv4 provides gridded population estimates with an output resolution of 30 arc-seconds (approximately 1 km at the equator) for the years 2000, 2005, 2010, 2015, and 2020 based on the results of the 2010 round of censuses, which occurred between 2005 and 2014. For more details about GPWv4 and to access the new data see http://sedac.ciesin.columbia.edu/data/collection/gpw-v4.
GPWv3 depicts the distribution of human population across the globe. GPWv3 provides globally consistent and spatially explicit human population information and data for use in research, policy making, and communications. This is a gridded, or raster, data product that renders global population data at the scale and extent required to demonstrate the spatial relationship of human populations and the environment across the globe.The purpose of GPW is to provide a spatially disaggregated population layer that is compatible with data sets from social, economic, and Earth science fields.The gridded data set is constructed from national or subnational input units (usually administrative units) of varying resolutions. The native grid cell resolution is 2.5 arc-minutes, or ~5km at the equator, although aggregates at coarser resolutions are also provided. Separate grids are available for population count and density per grid cell.
Population data estimates are provided for 1990, 1995, and 2000, and projected (in 2004, when GPWv3 was released) to 2005, 2010, and 2015. The projected grids were produced in collaboration with the United Nations Food and Agriculture Programme (FAO) as Population Count and Density Grid Future Estimates. There is also an extensive map collection that includes population density and sub-national administrative boundary maps (depicting the input units) at country, continental, and global levels. The Global Rural-Urban Mapping Project, Version One (GRUMPv1) data collection builds on GPW to construct a common geo-referenced framework of urban and rural areas by combining census data with satellite data.