WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)

-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

This map shows the population density of Mexico in relation to freshwater sources and water bodies.

This map shows the population density of Mexico in relation to freshwater sources and water bodies.

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

Race is a social and historical construct, and the racial categories counted by the census change over time so the process of constructing stable racial categories for these 50 years out of census data required complex and imperfect decisions. Here we have used historical research on early 20th century southern California to construct historic racial categories from the IPUMS full count data, which allows us to track groups that were not formally classified as racial groups in some census decades like Mexican, but which were important racial categories in southern California. Detailed explanation of how we constructed these categories and the rationale we used for the decisions we made can be found here. Layers are symbolized to show the percentage of each of the following groups from 1900-1940:AmericanIndian Not-Hispanic, AmericanIndian Hispanic, Black non-Hispanic, Black-Hispanic, Chinese, Korean, Filipino and Japanese, Mexican, Hispanic Not-Mexican, white non-Hispanic. The IPUMS Census data is messy and includes some errors and undercounts, making it hard to map some smaller populations, like Asian Indians (in census called Hindu in 1920) and creating a possible undercount of Native American populations. The race data mapped here also includes categories that may not have been socially meaningful at the time like Black-Hispanic, which generally would represent people from Mexico who the census enumerator classified as Black because of their dark skin, but who were likely simply part of Mexican communities at the time. We have included maps of the Hispanic not-Mexican category which shows very small numbers of non-Mexican Hispanic population, and American Indian Hispanic, which often captures people who would have been listed as Indian in the census, probably because of skin color, but had ancestry from Mexico (or another Hispanic country). This category may include some indigenous Californians who married into or assimilated into Mexican American communities in the early 20th century. If you are interested in mapping some of the other racial or ethnic groups in the early 20th century, you can explore and map the full range of variables we have created in the People's History of the IE IE_ED1900-1940 Race Hispanic Marriage and Age Feature layer.Suggested Citation: Tilton, Jennifer. People's History Race Ethnicity Dot Density Map 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. 2025Feature Layer CitationTilton, Jennifer, Tessa VanRy & Lisa Benvenuti. Race and Demographic Data 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. Additional contributing authors: Mackenzie Nelson, Will Blach & Andy Garcia Funding provided by: People’s History of the IE: Storyscapes of Race, Place, and Queer Space in Southern California with funding from NEH-SSRC Grant 2022-2023 & California State Parks grant to Relevancy & History. Source for Census Data 1900- 1940 Ruggles, Steven, Catherine A. Fitch, Ronald Goeken, J. David Hacker, Matt A. Nelson, Evan Roberts, Megan Schouweiler, and Matthew Sobek. IPUMS Ancestry Full Count Data: Version 3.0 [dataset]. Minneapolis, MN: IPUMS, 2021. Primary Sources for Enumeration District Linework 1900-1940 Steve Morse provided the full list of transcribed EDs for all 5 decades "United States Enumeration District Maps for the Twelfth through the Sixteenth US Censuses, 1900-1940." Images. FamilySearch. https://FamilySearch.org: 9 February 2023. Citing NARA microfilm publication A3378. Washington, D.C.: National Archives and Records Administration, 2003. BLM PLSS Map Additional Historical Sources consulted include: San Bernardino City Annexation GIS Map Redlands City Charter Proposed with Ward boundaries (Not passed) 1902. Courtesy of Redlands City Clerk. Redlands Election Code Precincts 1908, City Ordinances of the City of Redlands, p. 19-22. Courtesy of Redlands City Clerk Riverside City Charter 1907 (for 1910 linework) courtesy of Riverside City Clerk. 1900-1940 Raw Census files for specific EDs, to confirm boundaries when needed, accessed through Family Search. If you have additional questions or comments, please contact jennifer_tilton@redlands.edu.

This collection contains Environmental Response Management Application (ERMA) GIS layers used as part of the Programmatic Damage Assessment and Restoration Plan (PDARP), including outputs from Synthetic Aperture Radar (SAR) imagery, helicopter flights surveys (observations) of marine mammal and turtles, Mississippi Canyon 252 wellhead location, wellhead buffers, and supporting bathymetric contour data, infrared and photographic images from EPA's airborne spectral photometric environmental collection technology (ASPECT) with geospatial, chemical and radiological information, boom-related response observations, nearshore tissue and sediment samples, forensic and Total Polycyclic Aromatic Hydrocarbon (TPAH) results, stranded oil forensic classification data, and other types of chemistry data, Submerged Aquatic Vegetation (SAV) classifications, seabed sampling and transect data, sample locations for workplan cruises, deep-sea area injury toxicity results and total polycyclic aromatic hydrocarbon (TPAH) results, habitat injury zones, footprint impacts on mesophotic reef resources and other types of benthic habitat data, overflight imagery of the flight path for the NOAA King Air flights taken in October of 2010 and contains post-oiling images collection in support of Natural Resource Damage Assessment (NRDA) marsh monitoring, turtle survey overflight observations, loggerhead sea turtle density grids, sea turtle capture observations and transect analysis, sea turtle strandings, as well as probabilities of oiling and other related datasets, trawl locations, Southeast Area Monitoring and Assessment Program (SEAMAP) plankton trawls, workplan cruise samples, and other related data, delineation of the areas impacted with additional fresh water due to the opening of the diversions in 2011 as part of the Deepwater Horizon oil spill response, surface shoreline oiling characteristics as observed by field surveys performed by Shoreline Cleanup Assessment Techniques (SCAT) teams, marine mammal surveys, observations, telemetry and abundance data including Cytochrome P450 (CYP) dolphin analysis, population and abundance datasets, telemetry, wildlife and aerial observations, bathymetry estimates, and other related Marine Mammal field observations and surveys, presence and spatial distribution of synthetic-based mud (SBM) in deep-sea sediments around the Macondo well, surface sediment, residual kriging, and other oiling analytical data, oyster recruitment and abundance sampling results, estimates of subtidal habitat, estimates of oyster resource, seafloor substrate mapping layers, percent cover, nearshore and subtidal quadrat abundance data, and other related datasets, shoreline exposure model for beach and marsh oiling, wave exposure, habitat classifications, wetland monitoring datasets, and related shoreline datasets, compilation of all the individual Texture Classifying Neural Network Algorithm (TCNNA) days from Synthetic Aperture Radar (SAR) satellite polygons, a variety of cumulative oiling datasets including the Texture Classifying Neural Network Algorithm (TCNNA) from Synthetic Aperture Radar (SAR) satellite polygon layers, burn locations, dispersant operation datasets including estimations of where aerial dispersants were applied via aerial flight paths, dispersant airport locations, daily flight tracks, and vessel dispersant tracks, as well as locations of subsurface dispersant data, marine mammal surveys, observations, telemetry and abundance data collected including synoptic surveys, helicopter surveys, Cytochrome P450 (CYP) dolphin analysis, population and abundance datasets, telemetry, wildlife and aerial observations, bathymetry estimates, other related marine mammal field observations and surveys, and sea turtle data, and other data related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico. Some of these data were collected during the response to the Mississippi Canyon 252 Deepwater Horizon oil spill in the Northern Gulf of Mexico.

This dataset contains records of Gulf of Mexico (GOM) blue crab (Callinectes sapidus), white shrimp (Litopenaeus setiferus), brown shrimp (Farfantepenaeus aztecus), and fishes which can be used to quantify their population abundances and distributions. The data set contains existing data as a baseline and supplemental data from continued sampling. It contains records of early life stage blue crab, white shrimp, brown shrimp, and fishes (measurements and counts) from beach seine and trawl samples across the north GOM in the central Gulf States that were collected using standardized sampling methods. Data also include habitat assessments such as descriptions, georeferencing information, and abiotic factors (DO, salinity, temperature).