To provide annual global surface concentrations (micrograms per cubic meter) of all composition ground-level fine particulate matter less than or equal to 2.5 microns in diameter (PM2.5) for large-scale health and environmental research.

To provide national and subnational estimates of SDG indicator 7.1.1, the proportion of the population with access to electricity, produced using global open data.

To provide an annual global surface of concentrations (micrograms per cubic meter) of all composition ground-level fine particulate matter of 2.5 micrometers or smaller (PM2.5) for large-scale health and environmental 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 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 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 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 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 data that can be used to calculate trace gas and aerosol emissions, due to fires; monitor and assess national efforts to manage emissions.

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 continuous surface of NO2 concentrations for health and environmental research.

To provide data that can be used in land cover and land use change (LCLUC) studies, agricultural applications, and to assist with policy-making in regards to sustainable agricultural intensification.

To provide high spatial resolution estimates of global urban extent derived from global 30m Landsat satellite data for the target year 2010 and a companion dataset to the Global Man-made Impervious Surface (GMIS) dataset.

To provide high spatial resolution estimates of global man-made imperviousness for the target year 2010, derived from global 30m Landsat satellite data and a companion dataset to the Global Human Built-up And Settlement Extent (HBASE) dataset.

To provide a global data set of average summer daytime maximum/nighttime minimum land surface temperatures (LSTs) for urban extents, as well as the LST difference between the urban area and the buffer.

To provide raster representations of global summer daytime maximum and nighttime minimum surface temperature for studies related to human health and climate change.

To provide information on anthropogenic transformation of the biosphere circa 1700 for global land use studies and research on human-environment interactions.

To provide information on anthropogenic transformation of the biosphere circa 1800 for global land use studies and research on human-environment interactions.

To provide information on anthropogenic transformation of the biosphere circa 2000 for global land use studies and research on human-environment interactions.