Global gridded multi-temporal datasets to support human population distribution modelling

Population distributions across countries and regions exhibit significant spatial and temporal variability. This variation highlights the need for high-resolution, small-area demographic data to address the challenges posed by shifting population dynamics, urbanization, and migration. Small area population modelling, particularly the production of gridded population estimates, has advanced rapidly over the past decade. Gridded population estimates rely heavily on the availability of detailed geospatial ancillary datasets to capture, inform and explain the variabilities in population densities and distributions at small area scales, enabling the disaggregation from areal unit-based counts. Here we describe an extensive geospatial collection of annual, high resolution, spatio-temporally harmonised, global datasets aimed at driving improvements in mapping small area population density variation. This article presents the spatio-temporal harmonisation process that results in an open access repository of 73 individual gridded datasets addressing topography, climate, nighttime lights, land cover, inland water, infrastructure, protected areas as well as the built-up environment on a global level at a spatial resolution of 3 arc-seconds (approximately 100 metres). Datasets are available as annual time series from 2015 up to and including at least 2020, and as recent as 2023 where source datasets allow. Such datasets not only support population modelling but also applications across environmental, economic, and health sectors, supporting informed policy-making and resource allocation for sustainable development.