WorldPop provides high resolution, open and contemporary data on human population distributions, allowing accurate measurement of local population distributions, compositions, characteristics, growth and dynamics, across national and regional scales. WorldPop datasets include estimates of numbers of people residing in each 100 x 100 m grid cell and their age/sex structures for every low and middle income country. Through integrating census, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities from 2000-2020 are produced, along with accompanying metadata and peer-reviewed academic papers on methods. Where census data are outdated or unreliable, satellite and survey-based population estimation approaches are being implemented in collaboration with national statistical offices, largely as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) program.

The WorldPop Global data collection includes population surfaces for total populations (both adjusted to match UN national estimates, and left unadjusted) as well as breakdowns by age and sex classes, at annual time-steps between 2000 and 2020, with a spatial resolution of 3 arc seconds (approximately 100 m at the equator). Seamless global layers are implemented using consistent analytical methods and are accompanied by metadata outlining inputs and quality assessments.