The Sub-global Scenarios that Extend the Global SSP Narratives: Literature Database, Version 1, 2014-2021 consists of 37 columns of bibliographic data, methodological and analytical insights, from 155 articles published from 2014 to 2021 that extended the narratives of global SSPs. Local and regional scale Shared Socioeconomic Pathways (SSPs) have grown largely in addressing Climate Change Impact, Adaptation, and Vulnerability (CCIAV) assessments at sub-global levels. Common elements of these studies, besides their focus on CCIAV, are the use of both quantitative and qualitative elements of the SSPs. To explore and learn from current literature on novel methods and insights on extending SSPs, the sub-global extended SSPs literature database is constructed in the research for analyses. The database was developed in four stages: searches; screening; data extraction; and coding. The search stage incorporated three approaches: using a search string in three academic databases (Scopus, Web of Science Core Collection, ScienceDirect); a targeted search of a specific relevant database (ICONICS); and a targeted selection in Google Scholar of all papers that cited the publication of the global SSP narratives. In the screening step, criteria were assessed for full-text papers for eligibility including relevant typologies, methodologies, and other criteria. Finally, data from eligible papers was extracted and entered in a coding framework in an Excel workbook spreadsheet. The coding framework resulted in 37 columns to systematize coding of data from the 155 papers selected along several different dimensions, including categories of papers or analysis, several subcategories for SSP Applications and SSP Extensions, specific SSPs used, specific Representative Concentration Pathways (RCPs) used, typologies of extensions of qualitative and quantitative SSPs, and the types of models and nature of the extended SSPs.

This data set consists of roads, drainage, railroads, utilities, and population center information in readily usable vector format for the land area of the Former Soviet Union. The purpose of this dataset was to create a completely intact vector layer which could be readily used to aid in mapping efforts for the area of the FSU. These five vector data layers were assembled from the Digital Chart of the World (DCW), 1993. Individual record attributes were stored for population centers only. Vector maps for the FSU are in ArcView shapefile format.

This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003). This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles.

This data set contains the boundaries of the four major cities in the Northern Ecuadorian Amazon, the locations of primary communities in the colonist settlement area, and the locations of the road network, circa 2002. This area in northeastern Ecuador, know as the northern Oriente of Ecuador, borders the Andes Mountains and contains the headwaters of the Amazon River.The road network was originally digitized from 1:50,000 scale topographic maps from 1990. The surface attributes for the majority of the roads have been updated based on later remote sensing and field observations from 1999 and 2002. There are three compressed (*.zip) files with this data set.

The SDG Indicator 9.1.1: The Rural Access Index (RAI), 2023 Release data set, part of the SDGI collection, measures the proportion of the rural population who live within 2 kilometers of an all-season road for a given statistical area. UN SDG 9 is "build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation". Addressing inadequate access to roads, especially in rural areas, is critical to achieving SDG 9. According to the UN Sustainable Transport, Sustainable Development 2021 Interagency Report, sustainable transportation helps to eliminate poverty, promote food security, improve access to key health services, increase trade competitiveness, and bolster human rights. As one measure of progress towards SDG 9, the UN has established SDG indicator 9.1.1. The indicator was computed as the proportion of WorldPop gridded population within 2 kilometers to an OpenStreetMap (OSM) all-season road. The SDG indicator 9.1.1 data set provides estimates for the proportion of the rural population with access to all-season roads for 209 countries and 45,073 subnational Units. The data set is available at both national and level 2 subnational resolutions.

The SDG Indicator 7.1.1: Access to Electricity, 2023 Release data set, part of the Sustainable Development Goal Indicators (SDGI) collection, measures the proportion of the population with access to electricity for a given statistical area. UN SDG 7 is "ensure access to affordable, reliable, sustainable and modern energy for all". Tracking SDG 7: The Energy Progress Report estimated that in 2019, 759 million people around the world lacked access to electricity. Moreover, due to current policies and the detrimental effects of the COVID-19 crisis, it is predicted that by 2030, 660 million people will still not have access to electricity, with a majority of these people residing in Sub-Saharan Africa. As one measure of progress towards SDG 7, the UN agreed upon SDG indicator 7.1.1. The indicator was computed as the proportion of WorldPop gridded population located within illuminated areas defined by annual VIIRS Nighttime Lights Version 2 (VNL V2) data. The SDG indicator 7.1.1 data set provides estimates for the proportion of population with access to electricity for 206 countries and 45,979 level 2 subnational Units. The data set is available at both national and level 2 subnational resolutions.

The SDG Indicator 11.7.1: Urban Public Space, Availability and Access, 2023 Release, part of the SDGI collection, measures the average share of the built-up area of a city that is open space for public use for all. UN SDG 11 is "make cities and human settlements inclusive, safe, resilient and sustainable". Aside from environmental benefits, public space can also help improve public health, bolster commUnity, and encourage economic exchange. As one measure of progress towards SDG 11, the UN has established SDG indicator 11.7.1. The indicator was computed by measuring both the proportion of OpenStreetMap (OSM) public space within a given urban center and the proportion of WorldPop gridded population within 400 meters to Open Public Space (OPS). Cities were delineated using the European Commission Joint Research Centre (JRC) Urban Center Database (GHS-UCDB). The SDG indicator 11.7.1 data set provides estimates of the average share of the built-up area of cities that is open space for public use for all for 8,873 urban centers across 180 countries.

The SDG Indicator 11.2.1: Urban Access to Public Transport, 2023 Release, part of the SDGI collection, measures the proportion of the population in a city that has convenient access to public transport. UN SDG 11 is "make cities and human settlements inclusive, safe, resilient and sustainable". Improving access to public transport services is integral to achieving the objectives of SDG 11. According to the UN Sustainable Transport, Sustainable Development 2021 Interagency Report, "only about half the world's urban population have convenient access to public transport". The report highlights that access to sustainable transport can help reduce food insecurity, boost economies, empower women, and connect people to key health, education, and financial services. As one measure of progress towards SDG 11, the UN has established SDG indicator 11.2.1. The indicator was computed as the proportion of WorldPop gridded population within either 0.5 kilometer walking distance to a low-capacity OpenStreetMap (OSM) public transport point or 1 kilometer walking distance to a high-capacity OSM public transport point. Cities were delineated using the European Commission Joint Research Centre (JRC) Urban Center Database (UCDB). The SDG indicator 11.2.1 data set provides estimates for the proportion of population with convenient access to public transport for 5,749 urban centers across 178 countries.

This data set provides spatial data products with identified and classified locations of potential methane (CH4) emitting facilities and infrastructure in the South Coast Air Basin (SoCAB). These data products form a GIS-based mapping database designed to address shortcomings in current urban CH4 source inventories and is known as Vista Los Angeles (Vista-LA). SoCAB is the air shed for the greater Los Angeles urban area, which includes urbanized portions of the Los Angeles, Orange, Riverside, and San Bernardino Counties, California, USA. Vista-LA consists of detailed spatial maps for facilities and infrastructure in the SoCAB that are known or expected sources of CH4 emissions and illustrates the spatial distribution of potential CH4 sources, representing a first step towards developing an urban-scale CH4 emissions gridded inventory for the SoCAB. Vista-LA spatial data sets were created utilizing an assortment of publicly available data sources from local, state, and federal agencies for the years 2012 to 2017. The final Vista-LA database contains over 33,000 entries, which are presented as thirteen CH4 emitting infrastructure maps.

The Vulcan version 3.0 annual dataset provides estimates of annual carbon dioxide (CO2) emissions from the combustion of fossil fuels (FF) and CO2 emissions from cement production for the conterminous United States and the State of Alaska. Referred to as FFCO2, the emissions from Vulcan are categorized into 10 source sectors including; residential, commercial, industrial, electricity production, onroad, nonroad, commercial marine vessel, airport, rail, and cement. Data are gridded annually on a 1-km grid for the years 2010 to 2015. These data are annual sums of hourly estimates. Also provided are estimates of the upper 95% confidence interval and the lower 95% confidence interval boundaries for each emission estimate. For each uncertainty level, there are 10 individual sector files and one total file. These data are designed to be used as emission estimates in atmospheric transport modeling, policy, mapping, and other data analyses and applications.