69 datasets found
  1. a

    Population Density in the US 2020 Census

    • hub.arcgis.com
    • data-bgky.hub.arcgis.com
    Updated Jun 20, 2024
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    University of South Florida GIS (2024). Population Density in the US 2020 Census [Dataset]. https://hub.arcgis.com/maps/58e4ee07a0e24e28949903511506a8e4
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    Dataset updated
    Jun 20, 2024
    Dataset authored and provided by
    University of South Florida GIS
    Area covered
    Description

    This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  2. a

    Population density - Black - Map Service

    • hub.arcgis.com
    Updated Aug 15, 2012
    + more versions
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    Damian's Organization (2012). Population density - Black - Map Service [Dataset]. https://hub.arcgis.com/maps/damian::population-density-black-map-service
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    Dataset updated
    Aug 15, 2012
    Dataset authored and provided by
    Damian's Organization
    Area covered
    Description

    This map shows density surfaces derived from the 2010 US Census block points.This data shows % of people who identified themselves as 'single race' and 'Black'The block points were interpolated using the density function to a 2km x 2km grid of the continental US (with water and coastal data masks). There are many stories in these Maps:- What is that clean North/South Line through the center? Why do so many people live East of that line?- Notice the paths of the towns in the west – why are they so linear? And it seems there is a pattern to the spaces between the towns, why?- Looking at the ethnic maps, what explains the patterns? Look at the % Native American map – what are the areas of higher values? (note I did not make a % Asian map as at this scale there was not enough % to show any significant clusters.)

  3. Population density in the U.S. 2023, by state

    • statista.com
    Updated Dec 3, 2024
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    Statista (2024). Population density in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/
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    Dataset updated
    Dec 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

  4. d

    Digital data sets describing population density in the conterminous US

    • catalog.data.gov
    • datadiscoverystudio.org
    • +2more
    Updated Sep 2, 2024
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    U.S. Geological Survey (2024). Digital data sets describing population density in the conterminous US [Dataset]. https://catalog.data.gov/dataset/digital-data-sets-describing-population-density-in-the-conterminous-us
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    Dataset updated
    Sep 2, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Contiguous United States, United States
    Description

    Grid of population density in the conterminous United States at a resolution of one kilometer. The grid was converted from an ASCII file obtained from the Consortium for International Earth Science Information Network (CIESIN).

  5. d

    Landing Page

    • datadiscoverystudio.org
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    Esri, Landing Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/3b65829b27374011a74f53c9c6742219/html
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    Authors
    Esri
    Area covered
    Description

    Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

  6. A

    United States: High Resolution Population Density Maps + Demographic...

    • data.amerigeoss.org
    csv +2
    Updated Nov 23, 2021
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    UN Humanitarian Data Exchange (2021). United States: High Resolution Population Density Maps + Demographic Estimates [Dataset]. https://data.amerigeoss.org/th/dataset/united-states-high-resolution-population-density-maps-demographic-estimates
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    geotiff(371290), geotiff(1776499), csv(739022265), geotiff(231977), geotiff(116587981), geotiff(1117383), geotiff(614476002), geotiff(304019), geotiff(2895), csv(483753848), geotiff(199544098), geotiff(224182623), geotiff(124627362), geotiff(237058), csv(472969656), geotiff(26946380), csv(489231061), geotiff(1228665), geotiff(405664), geotiff(550808683), geotiff(1532704), csv(487815277), geotiff(183428692), csv(685438176), csv(394330534), csv(485656695), geotiff(124039499), geotiff(469990091), geotiff(11461), csv(394996827), geotiff(34907364), geotiff(157250075), geotiff(3728), geotiff(170821611), geotiff(673517573), geotiff(1659759), geotiff(125397), geotiff(234451), geotiff(235352906), geotiff(93419790), csv(372023378), geotiff(5998), geotiff(48567), geotiff(52959901), geotiff(46501506), geotiff(61425), csv(474849010), geotiff(6551882), geotiff(390755), geotiff(115398457), geotiff(106036740), geotiff(115081607), geotiff(20024613), geotiff(235417782), geotiff(2093905), geotiff(6086942), gdal virtual format(16491), geotiff(48083), geotiff(1762232), geotiff(34651551), geotiff(273238), geotiff(30387688), geotiff(40913), geotiff(349586), geotiff(208940973), geotiff(1791166), geotiff(223427143), csv(371942136), geotiff(365873), geotiff(575702), csv(394139438), csv(394960076), geotiff(305108), geotiff(34077058), csv(599533500), geotiff(612496510), geotiff(671100977), geotiff(154041022)Available download formats
    Dataset updated
    Nov 23, 2021
    Dataset provided by
    UN Humanitarian Data Exchange
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    These high-resolution maps estimate not only the number of people living within 30-meter grid tiles, but also provide insights on demographics at unprecedentedly high resolutions. These maps aren’t built using Facebook data and instead rely on combining the power of machine vision AI with satellite imagery and census information.

  7. Population density in the United States 2022

    • statista.com
    Updated Jun 4, 2025
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    Statista (2025). Population density in the United States 2022 [Dataset]. https://www.statista.com/statistics/269965/population-density-in-the-united-states/
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    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, the population density in the United States remained nearly unchanged at around 36.43 inhabitants per square kilometer. Nevertheless, 2022 still represents a peak in the population density in the United States. Population density refers to the average number of residents per square kilometer of land across a given country or region. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like Mexico.

  8. a

    2010 Population Density in the United States

    • hub.arcgis.com
    Updated May 26, 2017
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    ArcGIS Living Atlas Team (2017). 2010 Population Density in the United States [Dataset]. https://hub.arcgis.com/maps/arcgis-content::2010-population-density-in-the-united-states/about
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    Dataset updated
    May 26, 2017
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map shows the population density and total population in the United States in 2010. This is shown by state, county, tract, and block group. The color shows the population per square mile (population density), while the size of each feature shows the total population living there. This is a valuable way to represent population by understanding the quantity and density of the people living there. Areas with high population density are more tightly packed, while low population density means the population is more spread out.The map shows this pattern for states, counties, tracts, and block groups. There is increasing geographic detail as you zoom in, and only one geography is configured to show at any time. The data source is the US Census Bureau, and the vintage is 2010. The original service and data metadata can be found here.

  9. USA Urban Areas

    • data.lojic.org
    • atlas.eia.gov
    • +4more
    Updated Apr 22, 2014
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    Esri (2014). USA Urban Areas [Dataset]. https://data.lojic.org/maps/esri::usa-urban-areas/about
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    Dataset updated
    Apr 22, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of June 2023 and will retire in December 2025. A new version of this item is available for your use.The layers going from 1:1 to 1:1.5M present the 2010 Census Urbanized Areas (UA) and Urban Clusters (UC). A UA consists of contiguous, densely settled census block groups (BGs) and census blocks that meet minimum population density requirements (1000 people per square mile (ppsm) / 500 ppsm), along with adjacent densely settled census blocks that together encompass a population of at least 50,000 people. A UC consists of contiguous, densely settled census BGs and census blocks that meet minimum population density requirements, along with adjacent densely settled census blocks that together encompass a population of at least 2,500 people, but fewer than 50,000 people. The dataset covers the 50 States plus the District of Columbia within United States. The layer going over 1:1.5M presents the urban areas in the United States derived from the urban areas layer of the Digital Chart of the World (DCW). It provides information about the locations, names, and populations of urbanized areas for conducting geographic analysis on national and large regional scales. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to USA Census Urban Areas.

  10. W

    US Virgin Islands: High Resolution Population Density Maps + Demographic...

    • cloud.csiss.gmu.edu
    zip
    Updated Jul 23, 2019
    + more versions
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    UN Humanitarian Data Exchange (2019). US Virgin Islands: High Resolution Population Density Maps + Demographic Estimates [Dataset]. https://cloud.csiss.gmu.edu/uddi/es_AR/dataset/us-virgin-islands-high-resolution-population-density-maps-demographic-estimates
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    zip(130832), zip(168060), zip(130891), zip(168590), zip(167812), zip(131416), zip(178548), zip(131200), zip(130845), zip(168416), zip(130872), zip(130443), zip(167976), zip(167973)Available download formats
    Dataset updated
    Jul 23, 2019
    Dataset provided by
    UN Humanitarian Data Exchange
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    U.S. Virgin Islands
    Description

    The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery.

  11. a

    Race in the US by Dot Density

    • hub.arcgis.com
    • coronavirus-resources.esri.com
    • +1more
    Updated Jan 10, 2020
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    ArcGIS Living Atlas Team (2020). Race in the US by Dot Density [Dataset]. https://hub.arcgis.com/maps/71df79b33d4e4db28c915a9f16c3074e
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This 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?

  12. c

    2012 11: Popular Vote Density Map 2012 Presidential Election Results by...

    • opendata.mtc.ca.gov
    Updated Nov 28, 2012
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    MTC/ABAG (2012). 2012 11: Popular Vote Density Map 2012 Presidential Election Results by County [Dataset]. https://opendata.mtc.ca.gov/documents/9dff27c82bd8468c998675d3268bbf48
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    Dataset updated
    Nov 28, 2012
    Dataset authored and provided by
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The typical statewide or county-wide red/blue map (shown at left) depicts presidential voting results on a winner-take-all basis, so they award an entire geographical area to the Republican or Democratic candidate no matter how close the actual vote tally The large map in the attachment factors in both the percentage of the popular vote won by each candidate as well as the population density of each county. So, the sparsely populated Great Plains and Rocky Mountain West are shown in a much lighter color than the Eastern Seaboard, and the map as a whole is more purple than either red or blue. Perhaps the United States is less divided than some maps would lead us to believe.

  13. M

    High Resolution Population Density Maps - Africa

    • catalog.midasnetwork.us
    tiff, zip
    Updated Jul 12, 2023
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    MIDAS Coordination Center (2023). High Resolution Population Density Maps - Africa [Dataset]. https://catalog.midasnetwork.us/collection/290
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    zip, tiffAvailable download formats
    Dataset updated
    Jul 12, 2023
    Dataset authored and provided by
    MIDAS Coordination Center
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    Africa
    Variables measured
    age-stratified, phenotypic sex, population demographic census
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    The dataset is a zip file that contains 28 cloud optimized tiff files that cover the continent of Africa. Each of the 28 files represents a region or area - these are not divided by country. These 28 tiff files represent 2015 population estimates. However, please note that many of the country-level files include 2020 population estimates including: Angola, Benin, Botswana, Burundi, Cameroon, Cabo Verde, Cote d'Ivoire, Djibouti, Eritrea, Eswatini, The Gambia, Ghana, Lesotho, Liberia, Mozambique, Namibia, Sao Tome & Principe, Sierra Leone, South Africa, Togo, Zambia, and Zimbabwe. To create the high-resolution maps, machine learning techniques are used to identify buildings from commercially available satellite images then general population estimates are overlaid based on publicly available census data and other population statistics. The resulting maps are the most detailed and actionable tools available for aid and research organizations.

  14. d

    Demographics for US Census Tracts - 2012 (American Community Survey...

    • catalog.data.gov
    • data.wu.ac.at
    Updated Feb 25, 2025
    + more versions
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    U.S. Environmental Protection Agency, Research Triangle Park (Publisher, Distributor) (2025). Demographics for US Census Tracts - 2012 (American Community Survey 2008-2012 Derived Summary Tables) [Dataset]. https://catalog.data.gov/dataset/demographics-for-us-census-tracts-2012-american-community-survey-2008-2012-derived-summary-tabl14
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    Dataset updated
    Feb 25, 2025
    Dataset provided by
    U.S. Environmental Protection Agency, Research Triangle Park (Publisher, Distributor)
    Area covered
    United States
    Description

    This map service displays data derived from the 2008-2012 American Community Survey (ACS). Values derived from the ACS and used for this map service include: Total Population, Population Density (per square mile), Percent Minority, Percent Below Poverty Level, Percent Age (less than 5, less than 18, and greater than 64), Percent Housing Units Built Before 1950, Percent (population) 25 years and over (with less than a High School Degree and with a High School Degree), Percent Linguistically Isolated Households, Population of American Indians and Alaskan Natives, Population of American Indians and Alaskan Natives Below Poverty Level, and Percent Low Income Population (Less Than 2X Poverty Level). The map service was created for inclusion in US EPA mapping applications.

  15. f

    Data from: Mapping population distribution from open address data:...

    • tandf.figshare.com
    pdf
    Updated Jun 6, 2023
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    Nelson Mileu; Margarida Queirós; Paulo Morgado (2023). Mapping population distribution from open address data: application to mainland Portugal [Dataset]. http://doi.org/10.6084/m9.figshare.21036719.v1
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    pdfAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Nelson Mileu; Margarida Queirós; Paulo Morgado
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Portugal
    Description

    Mapping population distribution remains a common need in various fields of studies. Several approaches and methodologies have been adopted to obtain high-resolution population distribution grids. The use of addresses data to obtain gridded population distribution maps emerges as one of the more recent and accurate approaches. The increasing dissemination and availability of geo-data and more specifically address data allow us to obtain updated, granular and high spatial resolution population distribution maps. This paper describes a bottom-up open addresses data mapping-based approach of gridded population distribution with a fine spatial resolution. Through a QGIS plugin, an adaptation of the housing unit methodology was implemented to obtain 500 m × 500 and 250 m × 250 m population grids for mainland Portugal. The results showed that the use of reliable addresses databases can generate gridded population distribution maps with a high degree of adjustment to reality.

  16. f

    Population density of Africa

    • data.apps.fao.org
    Updated Apr 7, 2021
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    (2021). Population density of Africa [Dataset]. https://data.apps.fao.org/map/catalog/us/search?keyword=population%20density
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    Dataset updated
    Apr 7, 2021
    Description

    Population density estimates per sqkm.

  17. A

    Canada's Population Density

    • data.amerigeoss.org
    • gimi9.com
    • +2more
    jpeg, pdf
    Updated Jul 22, 2019
    + more versions
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    Canada (2019). Canada's Population Density [Dataset]. https://data.amerigeoss.org/hr/dataset/showcases/11325935-3af3-543e-80d4-8cf6cb4900e2
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    pdf, jpegAvailable download formats
    Dataset updated
    Jul 22, 2019
    Dataset provided by
    Canada
    Area covered
    Canada
    Description

    Contained within the Atlas of Canada Poster Map Series, is a poster showing population density across Canada. There is a relief base to the map on top of which is shown all populated areas of Canada where the population density is great than 0.4 persons per square kilometer. This area is then divided into five colour classes of population density based on Statistics Canada's census divisions.

  18. d

    Google Map Data, Google Map Data Scraper, Business location Data- Scrape All...

    • datarade.ai
    Updated May 23, 2022
    + more versions
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    APISCRAPY (2022). Google Map Data, Google Map Data Scraper, Business location Data- Scrape All Publicly Available Data From Google Map & Other Platforms [Dataset]. https://datarade.ai/data-products/google-map-data-google-map-data-scraper-business-location-d-apiscrapy
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    May 23, 2022
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Macedonia (the former Yugoslav Republic of), Albania, United States of America, Switzerland, Bulgaria, Serbia, Svalbard and Jan Mayen, Denmark, Gibraltar, Japan
    Description

    APISCRAPY, your premier provider of Map Data solutions. Map Data encompasses various information related to geographic locations, including Google Map Data, Location Data, Address Data, and Business Location Data. Our advanced Google Map Data Scraper sets us apart by extracting comprehensive and accurate data from Google Maps and other platforms.

    What sets APISCRAPY's Map Data apart are its key benefits:

    1. Accuracy: Our scraping technology ensures the highest level of accuracy, providing reliable data for informed decision-making. We employ advanced algorithms to filter out irrelevant or outdated information, ensuring that you receive only the most relevant and up-to-date data.

    2. Accessibility: With our data readily available through APIs, integration into existing systems is seamless, saving time and resources. Our APIs are easy to use and well-documented, allowing for quick implementation into your workflows. Whether you're a developer building a custom application or a business analyst conducting market research, our APIs provide the flexibility and accessibility you need.

    3. Customization: We understand that every business has unique needs and requirements. That's why we offer tailored solutions to meet specific business needs. Whether you need data for a one-time project or ongoing monitoring, we can customize our services to suit your needs. Our team of experts is always available to provide support and guidance, ensuring that you get the most out of our Map Data solutions.

    Our Map Data solutions cater to various use cases:

    1. B2B Marketing: Gain insights into customer demographics and behavior for targeted advertising and personalized messaging. Identify potential customers based on their geographic location, interests, and purchasing behavior.

    2. Logistics Optimization: Utilize Location Data to optimize delivery routes and improve operational efficiency. Identify the most efficient routes based on factors such as traffic patterns, weather conditions, and delivery deadlines.

    3. Real Estate Development: Identify prime locations for new ventures using Business Location Data for market analysis. Analyze factors such as population density, income levels, and competition to identify opportunities for growth and expansion.

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    5. Retail Expansion: Determine optimal locations for new stores or franchises using Location Data and Address Data. Analyze factors such as foot traffic, proximity to competitors, and demographic characteristics to identify locations with the highest potential for success.

    6. Competitive Analysis: Analyze competitors' business locations and market presence for strategic planning. Identify areas of opportunity and potential threats to your business by analyzing competitors' geographic footprint, market share, and customer demographics.

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    [ Related tags: Map Data, Google Map Data, Google Map Data Scraper, B2B Marketing, Location Data, Map Data, Google Data, Location Data, Address Data, Business location data, map scraping data, Google map data extraction, Transport and Logistic Data, Mobile Location Data, Mobility Data, and IP Address Data, business listings APIs, map data, map datasets, map APIs, poi dataset, GPS, Location Intelligence, Retail Site Selection, Sentiment Analysis, Marketing Data Enrichment, Point of Interest (POI) Mapping]

  19. a

    Population Density Map - Map Service

    • hub.arcgis.com
    Updated Aug 15, 2012
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    Damian's Organization (2012). Population Density Map - Map Service [Dataset]. https://hub.arcgis.com/datasets/1607107bf62446fba9704ccf510d46ed_0
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    Dataset updated
    Aug 15, 2012
    Dataset authored and provided by
    Damian's Organization
    Area covered
    Description

    This map shows density surfaces derived from the 2010 US Census block points.The block points were interpolated using the density function to a 2km x 2km grid of the continental US (with water and coastal data masks). There are many stories in these Maps:- What is that clean North/South Line through the center? Why do so many people live East of that line?- Notice the paths of the towns in the west – why are they so linear? And it seems there is a pattern to the spaces between the towns, why?- Looking at the ethnic maps, what explains the patterns? Look at the % Native American map – what are the areas of higher values? (note I did not make a % Asian map as at this scale there was not enough % to show any significant clusters.)

  20. Distribution of Population 1851-1941

    • open.canada.ca
    • datasets.ai
    • +2more
    jpg, pdf
    Updated Mar 14, 2022
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    Natural Resources Canada (2022). Distribution of Population 1851-1941 [Dataset]. https://open.canada.ca/data/en/dataset/48a638ed-1850-55b9-9b2b-348d7ee1e5df
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    pdf, jpgAvailable download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Ministry of Natural Resources of Canadahttps://www.nrcan.gc.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    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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University of South Florida GIS (2024). Population Density in the US 2020 Census [Dataset]. https://hub.arcgis.com/maps/58e4ee07a0e24e28949903511506a8e4

Population Density in the US 2020 Census

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Dataset updated
Jun 20, 2024
Dataset authored and provided by
University of South Florida GIS
Area covered
Description

This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

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