The Global 1-km Downscaled Population Base Year and Projection Grids Based on the Shared Socioeconomic Pathways, Revision 01, data set consists of global urban, rural, and total
populaton for the base year 2000, and population projections at ten-year intervals for 2010-2100 at a resolution of 1-km (about 30 arc-seconds), consistent both quantitatively and qualitatively with the SSPs. This 1-km data set is a downscaled version of the one-eighth degree (7.5 arc-minutes) data published in Jones and O'Neill (2016).
The downscaling methods were published in Gao (2017). Spatial demographic data are key inputs for the analysis of land use, energy use, and emissions, as well as for the
assessment of climate change vulnerability, impacts, and adaptation. The SSPs are developed to support future climate and global change research and the Intergovernmental Panel
on Climate Change (IPCC) Sixth Assessment Report (AR6).

The West Africa Coastal Vulnerability Mapping: Demographic and Health Survey Data Sets present grids of maternal education levels and household wealth based on Demographic and Health Survey (DHS) cluster level data for ten West African countries. While the maternal education levels are comparable across countries, owing to different underlying indicators, the household wealth index is not. Education can directly influence risk perception, skills and knowledge and indirectly reduce poverty, improve health, and promote access to information and resources. When facing natural hazards or climate risks, educated individuals, households, and societies are assumed to be more empowered and more adaptive in their response to, preparation for, and recovery from disasters. Education is a key background indicator that helps contextualize a country's health and development situation. The household wealth index is a composite measure of a household's cumulative living standard. The wealth index is calculated using easy-to-collect data on a household's ownership of selected assets, such as televisions and bicycles, materials used for housing construction, and types of water access and sanitation facilities. Bayesian spatial interpolation methods were employed to create country level grids based on DHS cluster point data for each country. Data are from the following dates by country: Benin (2006), Cameroon (2011), Cote d'Ivoire (2012), Ghana (2008), Guinea (2012), Liberia (2011), Nigeria (2010), Sierra Leone (2008), and Togo (1998).

The Poverty Mapping Project: Poverty and Food Security Case Studies data set consists of small area estimates of poverty, inequality, food security and related measures for subnational administrative Units in Mexico, Ecuador, Kenya, Malawi, Bangladesh, Sri Lanka, Nigeria and Vietnam. These data come from country level cases studies that examine poverty and food security from a spatial analysis perspective. The data products include shapefiles (vector data) and tabular data sets (csv format). Additionally, a data catalog (xls format) containing detailed information and documentation is provided. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) and Centro Internacional de Agricultura Tropical (CIAT). The data set was originally produced by CIAT, International Maize and Wheat Improvement Center (CIMMYT), International Livestock Research Institute (ILRI), International Food Policy Research Institute (IFPRI), International Rice Research Institute (IRRI), International Water Management Institute (IWMI), and International Institute for Tropical Agriculture (IITA).

The Millennium Ecosystem Assessment: MA Scenarios provides data and information on population, income, cereal production and consumption, meat production and consumption, land cover, water stress, water availability, acidification and nitrogen deposition. These scenarios provide useful insight into the complex factors that drive ecosystem change, estimating the magnitude of regional pressures on ecosystems and critical uncertainties that could undermine sustainable development. They also provide an understanding of the importance of institutions and values as the long-range outlook for the world's ecosystems depends on the course taken by global and regional development in the coming decades. The integration of changing ecosystem conditions into the global scenarios was taken as both effects and causes.

The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land cover, land use, agriculture, food, energy and biodiversity data . This dataset was collated by IPCC from a variety of sources such as The World Bank, United Nations Environment Programme (UNEP), and Food and Agriculture Organization of the United Nations (FAO), and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

The India Village-Level Geospatial Socio-Economic Data Set: 1991, 2001 is a compilation of the finest level of administrative boundaries in India (village/town-level) and over 200 socio-economic variables collected during the Indian Census in 1991 and 2001. This data set was developed by digitizing village/town level boundaries from the official analog maps published by the Survey of India for 2001. This data set also utilized tabular data for 1991 and 2001 from the Primary Census Abstract (PCA) and Village Directory (VD) data series of the Indian census. The data are in UTM 44N projection and are distributed primarily as shapefiles. Separate files are provided for each of the 28 states (number of states during 1991 and 2001 census) and combined Union Territories for 1991 and 2001.

The Global Multihazard Proportional Economic Loss Risks is a 2.5 minute grid of a multihazard-based economic loss risk as a proportion of the economic productivity of the analytical Unit, the grid cell. Representation of multihazard risk is not based on a multihazard index but rather on combinations of hazard risk categories, drought, seismic, and hydro. The drought category includes drought only. The seismic category consists of earthquake and volcano hazards. Cyclones, floods, and landslides are included in the hydro category.

For each of the six hazards considered, a binary risk surface is constructed utilizing the three most-at-risk deciles of each hazard's global proportional economic loss risks data set (deciles 8-10). Each of the category risk surfaces are constructed by adding all the relevant hazard high-risk surfaces. These categorical risk surfaces are reclassified into binary high-risk surfaces. The combination of the category risk values forms a three digit identifier for determining those locations that are at higher-risk from multihazards. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Landslide Proportional Economic Loss Risk Deciles is a 2.5 minute grid of landslide hazard economic loss as proportions of Gross Domestic Product (GDP) per analytical Unit. Estimates of GDP at risk are based on regional economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into deciles, 10 class of an approximately equal number of grid cells of increasing risk. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Flood Total Economic Loss Risk Deciles is a 2.5 minute grid of global flood total economic loss risks. A process of spatially allocating Gross Domestic Product (GDP) based upon the Sachs et al. (2003) methodology is utilized. First the proportional contributions of subnational Units to their respective national GDP are determined using sources of various origins. The contribution rates are then applied to published World Bank Development Indicators to determine a GDP value for the subnational Unit. Once the national GDP has been spatially stratified into the smallest administrative Units available, GDP values for grid cells are derived using Gridded Population of the World, Version 3 (GPWv3) data of population distributions. A per capita contribution value is determined within each subnational Unit, and this value is multiplied by the population per grid cell. Once a GDP value has been determined on a per grid cell basis, then the regionally variable loss rate as derived from the historical records of EM-DAT is used to determine the total economic loss risks posed to a grid cell by flood hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10 with increasing risk) ranking of grid cells based upon the calculated economic loss risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Earthquake Total Economic Loss Risk Deciles is a 2.5 minute grid of global earthquake total economic loss risks. A process of spatially allocating Gross Domestic Product (GDP) based upon the Sachs et al. (2003) methodology is utilized. First the proportional contributions of subnational Units to their respective national GDP are determined using sources of various origin. The contribution rates are then applied to published World Bank Development Indicators to determine a GDP value for the subnational Unit. Once the national GDP has been spatially stratified into the smallest administrative Units available, GDP values for grid cells are derived using Gridded Population of the World, Version 3 (GPWv3) data population distributions. A per capita contribution value is determined within each subnational Unit, and then this value is multiplied by the population per grid cell. Once a GDP value has been determined on a per grid cell basis, then the regionally variable loss rate as derived from the historical records of EM-DAT is used to determine the total economic loss risks posed to a grid cell by earthquake hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10 with increasing risk) ranking of grid cells based upon the calculated economic loss risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).