The Global Drought Total Economic Loss Risk Deciles is a 2.5 minute grid of global drought 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 is 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 drought 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 Cyclone Proportional Economic Loss Risk Deciles is a 2.5 minute grid of cyclone 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 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 Effects of Climate Change on Global Food Production from SRES Emissions and Socioeconomic Scenarios is an update to a major crop modeling study by the NASA Goddard Institute for Space Studies (GISS). The initial study was published in 1997, based on output of HadCM2 model forced with greenhouse gas concentration from the IS95 emission scenarios in 1997. Results of the initial study are presented at SEDAC's Potential Impacts of Climate Change on World Food Supply: Data Sets from a Major Crop Modeling Study, released in 2001. The co-authors developed and tested a method for investigating the spatial implications of climate change on crop production. The Decision Support System for Agrotechnology Transfer (DSSAT) dynamic process crop growth models, are specified and validated for one hundred and twenty seven sites in the major world agricultural regions. Results from the crop models, calibrated and validated in the major crop-growing regions, are then used to test functional forms describing the response of yield changes in the climate and environmental conditions. This updated version is based on HadCM3 model output along with GHG concentrations from the Special Report on Emissions Scenarios (SRES). The crop yield estimates incorporate some major improvements: 1) consistent crop simulation methodology and climate change scenarios; 2) weighting of model site results by contribution to regional and national, and rainfed and irrigated production; 3) quantitative foundation for estimation of physiological CO2 effects on crop yields; 4) Adaptation is explicitly considered; and 5) results are reported by country rather than by Basic Linked System region. The data are produced by A. Iglesias and C. Rosenzweig and the maps are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

The Country-Level GDP and Downscaled Projections Based on the Special Report on Emissions Scenarios (SRES) A1, A2, B1, and B2 marker scenarios, 1990-2100, were developed using the 1990 base year GDP (Gross Domestic Product) from national accounts database available from the UN Statistics Division. SRES regional GDP growth rates were calculated from 1990 to 2100 based on the SRES marker model regional data and applied uniformly to each country that fell within the SRES-defined regions. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

The China County-Level Data on Provincial Economic Yearbooks, Keyed To 1:1M GIS Map consists of socioeconomic and boundary data for the administrative regions of China for 1990 and 1991. The socioeconomic data includes natural resources, population, employment, investment, wage, public finance, price, people's livelihood, agriculture, industry, energy, production, transportation, telecommunication, construction, trade, tourism, environmental protection, education, science, patents, culture, sports, health care, and social welfare. The boundary data are at a scale of one to one million (1:1M) at the county level. This data set is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project, University of Michigan Center of China Studies (CCS), and the Center for International Earth Science Information Network (CIESIN).

The West Africa Coastal Vulnerability Mapping: Social Vulnerability Indices data set includes three indices: Social Vulnerability, Population Exposure, and Poverty and Adaptive Capacity. The Social Vulnerability Index (SVI) was developed using six indicators: population density (2010), population growth (2000-2010), subnational poverty and extreme poverty (2005), maternal education levels circa 2008, market accessibility (travel time to markets) circa 2000, and conflict data for political violence (1997-2013). Because areas of high population density and growth (high vulnerability) are generally associated with urban areas that have lower levels of poverty and higher degrees of adaptive capacity (low vulnerability), to some degree, the population factors cancel out the poverty and adaptive capacity indicators. To account for this, the data set includes two sub-indices, a Population Exposure Index (PEI), which only includes population density and population growth; and a Poverty and Adaptive Capacity Index (PACI), composed of subnational poverty, maternal education levels, market accessibility, and conflict. These sub-indices are able to isolate the population indicators from the poverty and conflict metrics. The indices represent Social Vulnerability in the West Africa region within 200 kilometers of the coast.

The West Africa Coastal Vulnerability Mapping: Gridded Subset of Sub-national Poverty and Extreme Poverty Prevalence represents the HarvestChoice Subnational Poverty and Extreme Poverty Prevalence data set as a one kilometer raster, and includes values within 200 kilometers of the coast. Poverty levels affect the "defenselessness" of populations in the low elevation coastal zone. These data were developed by the Harvest Choice project funded by the Bill and Melinda Gates Foundation. Harvest Choice measured 2005 poverty levels using 2005 purchasing power parity data for two thresholds: $1.25/day and $2/day international poverty lines. The $2/day threshold was selected for this mapping exercise.

The Poverty Mapping Project: Global Subnational Prevalence of Child Malnutrition data set consists of estimates of the percentage of children with weight-for-age z-scores that are more than two standard deviations below the median of the NCHS/CDC/WHO International Reference Population. Data are reported for the most recent year with subnational information available at the time of development. The data products include a shapefile (vector data) of percentage rates, grids (raster data) of rates (per thousand in order to preserve precision in integer format), the number of children under five (the rate denominator), and the number of underweight children under five (the rate numerator), and a tabular data set of the same and associated data. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

The Poverty Mapping Project: Global Subnational Infant Mortality Rates data set consists of estimates of infant mortality rates for the year 2000. The infant mortality rate for a region or country is defined as the number of children who die before their first birthday for every 1,000 live births. The data products include a shapefile (vector data) of rates, grids (raster data) of rates (per 10,000 live births in order to preserve precision in integer format), births (the rate denominator) and deaths (the rate numerator), and a tabular data set of the same and associated data. Over 10,000 national and subnational Units are represented in the tabular and grid data sets, while the shapefile uses approximately 1,000 Units in order to protect the intellectual property of source data sets for Brazil, China, and Mexico. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

The Poverty Mapping Project: Small Area Estimates of Poverty and Inequality data set consists of consumption-based poverty, inequality and related measures for subnational administrative Units in approximately twenty countries throughout Africa, Asia, Europe, North America, and South America. These measures are derived on a country-level basis from a combination of census and survey data using small area estimates techniques. The collection of data have been compiled, integrated and standardized from the original data providers into a unified spatially referenced and globally consistent data set. The data products include shapefiles (vector data), tabular data sets (csv format), and centroids (csv file with latitude and longitude of a geographic Unit and associated poverty estimates). 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) in collaboration with a number of external data providers.