These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom Foreign, Commonwealth & Development Office (OPP1182425). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

This work provides an estimate of the geographic distribution of the population of Mozambique in 2017. The outputs are intended as an interim population product to support ongoing development and operations work until such time as the official 2017 Population and Housing Census results are available in a spatial gridded format. At that time, this interim gridded population layer will be superseded and users will be advised to use the official gridded population release from INE.

For further details, please, read MOZ_population_v1_1_README.pdf

Recommended citation Bondarenko M, Jones P, Leasure D, Lazar AN, Tatem AJ. 2020. Census disaggregated gridded population estimates for Mozambique (2017), version 1.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00672

The U.S. Environmental Protection Agency (EPA) National Priorities List (NPL) Sites Point Data with CIESIN Modifications, Version 2 is a modified version of the 2014 EPA NPL list. It includes all the sites that are proposed, currently on, or deleted from the Final NPL as of February 27, 2014. CIESIN has fixed eleven of the original coordinates by correcting latitude or longitude coordinates. It contains the point locations, including the eleven corrections, for 1,747 U.S. hazardous waste sites on the National Priorities List (NPL) of EPA's Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) for the fifty states, Puerto Rico, and 4 other territorial areas plus the now independent Palau, Federated States of Micronesia. The sites in CERCLIS are also known as Superfund Sites. The NPL is intended primarily to guide the EPA in determining which sites warrant further investigation.

The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated data sets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).

The Agency for Toxic Substances and Disease Registry (ATSDR) Hazardous Waste Site Polygon Data with CIESIN Modifications, Version 2 is a database providing georeferenced data for 1,572 National Priorities List (NPL) Superfund sites. These were selected from the larger set of the ATSDR Hazardous Waste Site Polygon Data, Version 2 data set with polygons from May 26, 2010. The modified data set contains only sites that have been proposed, currently on, or deleted from the final NPL as of October 25, 2013. Of the 2,080 ATSDR polygons from 2010, 1,575 were NPL sites but three sites were excluded - 2 in the Virgin Islands and 1 in Guam. This data set is modified by the Columbia University Center for International Earth Science Information Network (CIESIN). The modified polygon database includes all the attributes for these NPL sites provided in the ATSDR GRASP Hazardous Waste Site Polygon database and selected attributes from the EPA List 9 Active CERCLIS sites and SCAP 12 NPL sites databases. These polygons represent sites considered for cleanup under the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA or Superfund). The Geospatial Research, Analysis, and Services Program (GRASP, Division of Health Studies, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention) has created site boundary data using the best available information for those sites where health assessments or consultations have been requested.

This dataset contains population estimates, by age and sex, per 30 arc-second grid cell consistent with national censuses and population registers. There is one image for each modeled age and sex category based on the 2010 round of Census. General Documentation The Gridded Population of World Version 4 (GPWv4), Revision …

A consortium of groups, led by International Council for Science's Committee on Data for Science and Technology (ICSU-CODATA) Global Roads Data Development Task Group, is developing a digital, public domain global road map under the name Global Roads Open. This dataset includes just Combating Wildlife Trafficking countries.

The Gridded Population of the World, Version 3 (GPWv3): Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean Unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean Unit size grids provides a quantitative surface that indicates the size of the input Unit(s) from which population count and density grids are derived..GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).

The current version supersedes GRID3 COD - Settlement Extents v3.0; the following changes were made:Corrections on imputed values for building count and building areas.Corrections on probability values from field-collected dataEdits in the Data Release NotesThe two layers contained within the GRID3 COD - Settlement Extents v3.1 include:GRID3_COD_settlement_extents_v3_1.gpkg: a spatial layer representing settlement polygons.GRID3_COD_settlement_grid_v3_1.gpkg: a spatial layer representing the centroids of settled grid cells.For more information on data inputs, methodology, and codebooks please see the Data Release Notes. Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 COD - Settlement Extents v3.1. New York: GRID3. https://doi.org/10.7916/d6gy-yh28. Accessed [DAY MONTH YEAR].Terms of use:Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use.Copyright 2024. The Trustees of Columbia University in the City of New York.Data license:The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode)Contacts and data queries:The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu

Country code identification (ccid) DEM provided as 1201x1201 pixel tiles, based on GADM v2.0 country boundaries (http://www.gadm.org/) with some island ccid, internal country boundary, and enclave amendments from gpwv4 (http://www.ciesin.columbia.edu/data/gpw-v4) and GADM v2.8, and Viewfinder Panorama SRTM based 3" topography tiles (http://viewfinderpanoramas.org/).

description: The Global 15x15 Minute Grids of the Downscaled Population Based on the Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990 and 2025, are geospatial distributions of the downscaled population per unit area (population densities). These global grids were generated using the Country-level Population and Downscaled Projections Based on the SRES B2 Scenario, 1990-2100 dataset, and CIESIN's Gridded Population of World, Version 2 (GPWv2) dataset as the base map. The 1990 GPW was used as the base distribution and the country-level downscaled projections were used to replace population estimates of 1990 in GPW and 2025. The fractional distribution of the population at each grid cell is the same as the 1990 GPW, sub-nationally. This dataset is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).; abstract: The Global 15x15 Minute Grids of the Downscaled Population Based on the Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990 and 2025, are geospatial distributions of the downscaled population per unit area (population densities). These global grids were generated using the Country-level Population and Downscaled Projections Based on the SRES B2 Scenario, 1990-2100 dataset, and CIESIN's Gridded Population of World, Version 2 (GPWv2) dataset as the base map. The 1990 GPW was used as the base distribution and the country-level downscaled projections were used to replace population estimates of 1990 in GPW and 2025. The fractional distribution of the population at each grid cell is the same as the 1990 GPW, sub-nationally. This dataset is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

Data sets and related data products and services provided by SEDAC managed by the NASA Earth Science Data and Information System (ESDIS) project. SEDAC is one of the Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs), part of the ESDIS project.

About SEDAC. http://sedac.ciesin.columbia.edu/about, Retrieved 27 Oct 2020.

This current version supersedes the GRID3 NGA - Health Facilities dataset; the following changes were made: Change of data schemaUpdate of data inputs to incorporate records from the Nigeria Health Facility Registry (HFR, 2024).Schema and data attributes’ standardization based on national guidelines For more information on the methodology and data sources used during the production of this data, see the Data Release Notes.Dataset citation Center for Integrated Earth System Information (CIESIN), Columbia University 2024. GRID3 NGA - Health Facilities v2.0. New York: GRID3. https://doi.org/10.7916/kv1n-0743. Accessed [DAY MONTH YEAR].Contacts and data queriesThe authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu

The "GRID3 Republic of the Congo Settlement Extents, Version 01" supersedes "GRID3 Republic of the Congo Settlement Extents Version 01, Alpha."

The dataset consists of settlement extents across Republic of the Congo, as well as accompanying population estimates for each settlement extent.

This data product contains all information contained in the previous “GRID3 Republic of the Congo Settlement Extents, Version 01 Alpha” product, with updates. Updates in this version include: a single settlement extent feature class (alpha version contains the same data in three separate feature class layers: BUAs, SSAs, and hamlets) and new population estimate fields (Population and Pop_UN_adj) for each settlement extent.

This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Republic of the Congo Settlement Extents, Version 01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-x820-2g93 . Accessed DAY MONTH YEAR.

Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class.

This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Côte d'Ivoire Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-y7wv-4398 . Accessed DAY MONTH YEAR.

The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. The purpose is to provide an open access, well documented global data set of roads between settlements using a consistent data model (UNSDI-T v.2) which is, to the extent possible, topologically integrated.Dataset SummaryThe Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.Documentation for the Global Roads Open Access Data Set, Version 1 (gROADSv1)Recommended CitationCenter for International Earth Science Information Network - CIESIN - Columbia University, and Information Technology Outreach Services - ITOS - University of Georgia. 2013. Global Roads Open Access Data Set, Version 1 (gROADSv1). Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4VD6WCT. Accessed DAY MONTH YEAR.

description: The Urban Place GIS Coverage of Mexico is a vector based point Geographic Information System (GIS) coverage of 696 urban places in Mexico. Each Urban Place is geographically referenced down to one tenth of a minute. The attribute data include time-series population and selected census/geographic data items for Mexican urban places from from 1921 to 1990. The cartographic data include urban place point locations on a state boundary file of Mexico. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Instituto Nacional de Estadistica Geografia e Informatica (INEGI) and the Environmental Research Institute (ERI) of Michigan. (Suggested Usage: To provide an urban place GIS coverage of Mexico.); abstract: The Urban Place GIS Coverage of Mexico is a vector based point Geographic Information System (GIS) coverage of 696 urban places in Mexico. Each Urban Place is geographically referenced down to one tenth of a minute. The attribute data include time-series population and selected census/geographic data items for Mexican urban places from from 1921 to 1990. The cartographic data include urban place point locations on a state boundary file of Mexico. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Instituto Nacional de Estadistica Geografia e Informatica (INEGI) and the Environmental Research Institute (ERI) of Michigan. (Suggested Usage: To provide an urban place GIS coverage of Mexico.)

The High Resolution Settlement Layer (HRSL) provides estimates of human population distribution at a resolution of 1 arc-second (approximately 30m) for the year 2015. The population estimates are based on recent census data and high-resolution (0.5m) satellite imagery from DigitalGlobe. The population grids provide detailed delineation of settlements in both urban and rural areas, which is useful for many research areas—from disaster response and humanitarian planning to the development of communications infrastructure. The settlement extent data were developed by the Connectivity Lab at Facebook using computer vision techniques to classify blocks of optical satellite data as settled (containing buildings) or not. Center for International Earth Science Information Networks (CIESIN) at Earth Institute Columbia University used proportional allocation to distribute population data from subnational census data to the settlement extents. The data-sets contain the population surfaces, metadata, and data quality layers. The population data surfaces are stored as GeoTIFF files for use in remote sensing or geographic information system (GIS) software. The data can also be explored via an interactive map - http://columbia.maps.arcgis.com/apps/View/index.html?appid=ce441db6aa54494cbc6c6cee11b95917 Citation: Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. High Resolution Settlement Layer (HRSL). Source imagery for HRSL © 2016 DigitalGlobe.

Ivory Coast CI: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data was reported at 3.765 % in 2010. This records an increase from the previous number of 3.640 % for 2000. Ivory Coast CI: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data is updated yearly, averaging 3.765 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 3.874 % in 1990 and a record low of 3.640 % in 2000. Ivory Coast CI: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Land Use, Protected Areas and National Wealth. Population below 5m is the percentage of the total population living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted average;

This layer was created by Duncan Smith and based on work by the European Commission JRC and CIESIN. A description from his website follows:--------------------A brilliant new dataset produced by the European Commission JRC and CIESIN Columbia University was recently released- the Global Human Settlement Layer (GHSL). This is the first time that detailed and comprehensive population density and built-up area for the world has been available as open data. As usual, my first thought was to make an interactive map, now online at- http://luminocity3d.org/WorldPopDen/The World Population Density map is exploratory, as the dataset is very rich and new, and I am also testing out new methods for navigating statistics at both national and city scales on this site. There are clearly many applications of this data in understanding urban geographies at different scales, urban development, sustainability and change over time.

The two layers contained within the GRID3 GIN - Settlement Extents v3.0 include:GRID3_GIN_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons.GRID3_GIN_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells.The current version supersedes GRID3 GIN - Settlement Extents v2.0; the following changes were made:Development of a new methodology to derive building counts and settlement polygons with open data.Estimation of a probability value for settlement polygonsAddition of a building-area measureReplacement of degree of urbanization with classification based on built-up areas, small settlement areas, and hamletsElimination of building-count rangesElimination of variable comparing to previous versionsFor more information on data inputs, methodology, and codebooks please see the Data Release Notes.Recommended Citation:Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 GIN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/7nqp-pj27. Accessed [DAY MONTH YEAR].Terms of use:Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use.Copyright 2024. The Trustees of Columbia University in the City of New York.Data license:The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode).Contacts and data queries:The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu