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TwitterThis map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?
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TwitterExplore our new interactive population density maps for MSA, County, Tract, Block Group, Place, School District, and ZCTA geographies in Texas. These pop density maps are based on the latest ACS 5-Year estimates and TIGER/Line data. Inspired by a map of the same produced by the Texas Demography Center.
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TwitterThese data contain selected census tract level demographic indicators (estimates) from the 2015-2019 American Community Survey representing the population density by square mile (land area).
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TwitterCensus data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics
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TwitterThis app offers an interactive legend allowing users a more holistic experience with the 2016 Nigeria Population Density Map. In this app, unlike the web map, users can interact with the legend. By clicking on categories defined in the legend, they can focus on particular categories/ranges that are more relevant to them.
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TwitterThis layer shows the Hong Kong population density in 2021 Population Census. It is a subset of the census data 2021 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in XLSX format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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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.
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Population density 2024 (inhabitants per km²) per municipality Statistical data sources: INSEE Grand Est, IWEPS, Statistisches Landesamt Rheinland-Pfalz, Statistisches Amt Saarland Geodata sources: ACT Luxembourg 2024, IGN France 2022, GeoBasis-DE / BKG 2024, NGI-Belgium 2024. Harmonization: SIG-GR / GIS-GR 2024 Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=2434&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/4ba433fb-6c1e-459f-89ca-a2914eedfdaa This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Pop_density_WMS/guest with layer name(s): -Pop_density_2024
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows the distribution of population in what is now Canada circa 1851, 1871, 1901, 1921 and 1941. The five maps display the boundaries of the various colonies, provinces and territories for each date. Also shown on these five maps are the locations of principal cities and settlements. These places are shown on all of the maps for reference purposes even though they may not have been in existence in the earlier years. Each map is accompanied by a pie chart providing the percentage distribution of Canadian population by province and territory corresponding to the date the map is based on. It should be noted that the pie chart entitled Percentage Distribution of Total Population, 1851, refers to the whole of what was then British North America. The name Canada in this chart refers to the province of Canada which entered confederation in 1867 as Ontario and Quebec. The other pie charts, however, show only percentage distribution of population in what was Canada at the date indicated. Three additional graphs are included on this plate and show changes in the distribution of the population of Canada from 1867 to 1951, changes in the percentage distribution of the population of Canada by provinces and territories from 1867 to 1951 and elements in the growth of the population of Canada for each ten-year period from 1891 to 1951.
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TwitterPopulation density 2015 (inhabitants per km²), Lorraine: 2013
Territorial entities: arrondissements (Wallonie), zones d'emploi (Lorraine), cantons (Luxembourg), Kreise (Saarland, Rheinland-Pfalz)
Statistical data sources: INSEE Grand Est; SPF Economie; STATEC; Statistisches Landesamt Rheinland-Pfalz; Statistisches Amt Saarland. Harmonization: IBA / OIE 2016
Geodata sources: EuroGeographics EuroRegionalMap v3.0 - 2010. Harmonization: SIG-GR / GIS-GR 2016
Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=1732&opacities=1&bgLayer=basemap_2015_global
Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/4f71026c-4ab0-4153-a00d-2a5d34aae307
This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Pop_density_WMS/guest with layer name(s): -Pop_density_2015
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Population density 2024 (inhabitants per km²). Reference date: 01.01.2024 (Luxembourg and Wallonia), 31.12.2023 (Rhineland-Palatinate and Saarland), 01.01.2022 (Lorraine) Territorial entities: municipalities (Saarland, Wallonie), cantons (Luxembourg), EPCI (Lorraine), Verbandsgemeinden and verbandsfreie Städte und Gemeinden (Rheinland-Pfalz) Statistical data sources: DATer, INSEE Grand Est, IWEPS, Région Grand Est, STATEC, Statistisches Landesamt Rheinland-Pfalz, Statistisches Landesamt Saarland. Harmonization: SIG-GR / GIS-GR 2025 Geodata sources: GeoBasis-DE / BKG, IGN France, NGI-Belgium, ACT Luxembourg. Harmonization: SIG-GR / GIS-GR 2025 Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=2435&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/93569c33-a975-4885-9896-626cff07cfa0 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Pop_density_WMS/guest with layer name(s): -Pop_density_2024_infra
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We are pleased to announce that the GlobPOP dataset for the years 2021-2022 has undergone a comprehensive quality check and has now been updated accordingly. Following the established methodology that ensures the high precision and reliability, these latest updates allow for even more comprehensive time-series analysis. The updated GlobPOP dataset remains available in GeoTIFF format for easy integration into your existing workflows.
2021-2022 年的 GlobPOP 数据集经过全面的质量检查,现已进行相应更新。 遵循确保高精度和可靠性的原有方法,本次更新允许进行更全面的时间序列分析。 更新后的 GlobPOP 数据集仍以 GeoTIFF 格式提供,以便轻松集成到您现有的工作流中。
To reflect these updates, our interactive web application has also been refreshed. Users can now explore the updated national population time-series curves from 1990 to 2022. This can be accessed via the same link: https://globpop.shinyapps.io/GlobPOP/. Thank you for your continued support of the GlobPOP, and we hope that the updated data will further enhance your research and policy analysis endeavors.
交互式网页反映了人口最新动态,用户现在可以探索感兴趣的国家1990 年至 2022 年人口时间序列曲线,并将其与人口普查数据进行比较。感谢您对 GlobPOP 的支持,我们希望更新的数据将进一步加强您的研究和政策分析工作。
If you encounter any issues, please contact us via email at lulingliu@mail.bnu.edu.cn.
如果您遇到任何问题,请通过电子邮件联系我们。
Continuously monitoring global population spatial dynamics is essential for implementing effective policies related to sustainable development, such as epidemiology, urban planning, and global inequality.
Here, we present GlobPOP, a new continuous global gridded population product with a high-precision spatial resolution of 30 arcseconds from 1990 to 2020. Our data-fusion framework is based on cluster analysis and statistical learning approaches, which intends to fuse the existing five products(Global Human Settlements Layer Population (GHS-POP), Global Rural Urban Mapping Project (GRUMP), Gridded Population of the World Version 4 (GPWv4), LandScan Population datasets and WorldPop datasets to a new continuous global gridded population (GlobPOP). The spatial validation results demonstrate that the GlobPOP dataset is highly accurate. To validate the temporal accuracy of GlobPOP at the country level, we have developed an interactive web application, accessible at https://globpop.shinyapps.io/GlobPOP/, where data users can explore the country-level population time-series curves of interest and compare them with census data.
With the availability of GlobPOP dataset in both population count and population density formats, researchers and policymakers can leverage our dataset to conduct time-series analysis of population and explore the spatial patterns of population development at various scales, ranging from national to city level.
The product is produced in 30 arc-seconds resolution(approximately 1km in equator) and is made available in GeoTIFF format. There are two population formats, one is the 'Count'(Population count per grid) and another is the 'Density'(Population count per square kilometer each grid)
Each GeoTIFF filename has 5 fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below with the example filename:
GlobPOP_Count_30arc_1990_I32
Field 1: GlobPOP(Global gridded population)
Field 2: Pixel unit is population "Count" or population "Density"
Field 3: Spatial resolution is 30 arc seconds
Field 4: Year "1990"
Field 5: Data type is I32(Int 32) or F32(Float32)
Please refer to the paper for detailed information:
Liu, L., Cao, X., Li, S. et al. A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning. Sci Data 11, 124 (2024). https://doi.org/10.1038/s41597-024-02913-0.
The fully reproducible codes are publicly available at GitHub: https://github.com/lulingliu/GlobPOP.
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Population density 2023 (inhabitants per km²), Lorraine: 2021 Territorial entities: arrondissements (Lorraine, Wallonie), cantons (Luxembourg), Kreise (Saarland, Rheinland-Pfalz) Statistical data sources: Destatis, INSEE, Statbel, STATEC. Harmonization: IBA / OIE 2024 Geodata sources: GeoBasis-DE / BKG, IGN France, NGI-Belgium, ACT Luxembourg. Harmonization: SIG-GR / GIS-GR 2024 Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=2418&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/3ed89eb1-9a37-4b86-b793-126411751345 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Pop_density_WMS/guest with layer name(s): -Pop_density_2023
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TwitterThis layer shows dot density of the population by race and Hispanic origin - each race and Hispanic or Latino ethnicity is represented by a dot of the number of people who reported their race in each category. This is shown by 2020 census tract boundaries. This map is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are additional calculated attributes related to this topic, which can be mapped or used within analysis. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. This map uses services from these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available. For more information regarding the ACS vintage, table sources and data processing notes, please see the item page for the source map service.
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Population density 2013 (inhabitants per km²) Territorial entities: arrondissements (Wallonie), zones d'emploi (Lorraine), cantons (Luxembourg), Kreise (Saarland, Rheinland-Pfalz) Statistical data sources: INSEE Lorraine; SPF Economie; STATEC; Statistisches Landesamt Rheinland-Pfalz; Statistisches Amt Saarland. Harmonization: IBA / OIE 2014 Geodata sources: EuroGeographics EuroRegionalMap v3.0 - 2010. Harmonization: SIG-GR / GIS-GR 2014 Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=1713&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/747df575-4704-4016-b04f-d19d16d41298 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Pop_density_WMS/guest with layer name(s): -Pop_density_2013
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TwitterThis web map shows the Population distribution by sex in 2001 within the 18 districts of Hong Kong. It is a subset of the census data 2001 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Data.gov.hk at https://data.gov.hk.
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TwitterThis web map shows the Population distribution by Ethnicity in 2001 within the 18 districts of Hong Kong. It is a subset of the census data 2001 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Data.gov.hk at https://data.gov.hk.
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TwitterThis web map shows the Mid Year Population Density within the 18 districts of Hong Kong. It is a subset of data made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.
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TwitterThis web map shows the Population distribution by household sizes in 2016 within the 18 districts of Hong Kong. It is a subset of the census data 2016 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in XLSX format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.
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TwitterThe Atlas of the Biosphere is a product of the Center for Sustainability and the Global Environment (SAGE), part of the Gaylord Nelson Institute for Environmental Studies at the University of Wisconsin - Madison. The goal is to provide more information about the environment, and human interactions with the environment, than any other source.
The Atlas provides maps of an ever-growing number of environmental variables, under the following categories:
Human Impacts (Humans and the environment from a socio-economic perspective; i.e., Population, Life Expectancy, Literacy Rates);
Land Use (How humans are using the land; i.e., Croplands, Pastures, Urban Lands);
Ecosystems (The natural ecosystems of the world; i.e., Potential Vegetation, Temperature, Soil Texture); and
Water Resources (Water in the biosphere; i.e., Runoff, Precipitation, Lakes and Wetlands).
Map coverages are global and regional in spatial extent. Users can download map images (jpg) and data (a GIS grid of the data in ESRI ArcView Format), and can view metadata online.
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TwitterThis map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?