To provide a cumulative measure of human modification of terrestrial lands based on modeling the physical extents of 13 anthropogenic stressors and their estimated impacts using spatially-explicit global data sets.

To provide gridded data that identify the level of intensity and frequency of food insecurity over the 10 years between 2009 and 2019, as well as hotspot areas that have experienced consecutive food insecurity events, based on FEWS NET Food Security Data.

To provide high-resolution population and urban classification data for India for 2011.

To provide spatially-explicit data that relatively rank global land suitability referred to as Development Potential Indices (DPIs) for 13 sectors related to renewable energy, fossil fuels, mining and agriculture as an aid to conservation priority setting.

To provide a global gridded data set of commonly-used agricultural pesticides crucial to assess human and ecosystem exposure to potential toxicants for environmental modeling, assessment of agricultural chemical contamination and risk analysis, and other related research at global, regional, national, and local levels.

To provide global urban, rural, and total population base year and projection grids based on the Shared Socioeconomic Pathways (SSPs) data at a resolution of one-eighth degree (7.5 arc-minutes) for climate, socioeconomic, environmental, and other related research.

To provide global urban, rural, and total population base year and projection grids based on the Shared Socioeconomic Pathways (SSPs) data at a resolution of 1-km (about 30 arc-seconds) for climate, socioeconomic, environmental, and other related research.

To visualize changes in brightness and extent of global nighttime lights networks over two decades with improved radiometric accuracy and finer spatial resolution.

To provide a future development threat map based on combining these resources: agricultural expansion, urban expansion, conventional oil and gas, unconventional oil and gas, coal, mining, biofuels, solar, and wind.

To provide a global subnational map of infant mortality rate estimates for the year 2015, to be used by a wide user community in interdisciplinary studies of health, poverty, and the environment.

To provide data on changes in freshwater availability in order to better understand impacts on regional food supplies, human and ecosystem health, energy generation, and social unrest.

To provide representations of urban areas in the Continental U.S. in the year 2015 to support sustainable urban development planning in accordance with the growth of urban areas.

To provide satellite altimeter corrected digital elevation data for environmental, socioeconomic, climate and other related research, such as flood risk assessment, land deformations, landslide modelling, urban planning, and sea level rise impacts.

To provide data that can be used in independent spatial statistical analyses, construction of development-related indices, or in combination with remote sensing data in order to identify spatio-temporal patterns and/or changes in different demographic categories, such as male, female, urban, rural, level of education, etc.

To provide a vector (point) version of the input administrative units used in GPWv4 with population estimates, densities, 2010 basic demographic characteristics, and administrative name, area, and data context for use in data integration.

To provide estimates of population counts by age and sex for the year 2010, consistent with national censuses and population registers, as raster data to facilitate data integration.

To provide a raster representation of nation-states in GPWv4 for use in aggregating population data.

To provide estimates of population density for the years 2000, 2005, 2010, 2015, and 2020, based on counts consistent with national censuses and population registers with respect to relative spatial distribution, but adjusted to match United Nations country totals.

To provide pixel-level land and water surface area estimates.

To provide estimates of population density for the years 2000, 2005, 2010, 2015, and 2020, based on counts consistent with national censuses and population registers, as raster data to facilitate data integration.