To provide a polygon representation of urban areas with city or agglomeration name and time series population estimates.

To provide a literature database tracking the use of a global scenarios framework consisting of Shared Socioeconomic Pathways (SSPs), Representative Concentration Pathways (RCPs), and Shared Policy Assumptions (SPAs), for climate, socioeconomic, environmental, and other related research.

To provide subnational (county) population projection scenarios for the United States essential for understanding long-term demographic changes, planning for the future, and decision-making in a variety of applications.

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

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 describe changing population distribution and growth in Latin America and the Caribbean using spatially consistent and comparable units at a spatial resolution suitable to regional change analysis.

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 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 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 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 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.

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

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

To provide spatially explicit, historic, city-level population data from 3700 BC to AD 2000 for improved understanding of contemporary and historical urbanization trends.

To provide areas in the coastal zone of West Africa that may be particularly exposed to climate stressors owing to high population density.