Author: Joseph Kerski, post_secondary_educator, Esri and University of DenverGrade/Audience: high school, ap human geography, post secondary, professional developmentResource type: lessonSubject topic(s): population, maps, citiesRegion: africa, asia, australia oceania, europe, north america, south america, united states, worldStandards: All APHG population tenets. Geography for Life cultural and population geography standards. Objectives: 1. Understand how population change and demographic characteristics are evident at a variety of scales in a variety of places around the world. 2. Understand the whys of where through analysis of change over space and time. 3. Develop skills using spatial data and interactive maps. 4. Understand how population data is communicated using 2D and 3D maps, visualizations, and symbology. Summary: Teaching and learning about demographics and population change in an effective, engaging manner is enriched and enlivened through the use of web mapping tools and spatial data. These tools, enabled by the advent of cloud-based geographic information systems (GIS) technology, bring problem solving, critical thinking, and spatial analysis to every classroom instructor and student (Kerski 2003; Jo, Hong, and Verma 2016).

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?

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the Census tract 2022 boundary file in a GIS system to produce maps for 40 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

These 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).

Explore 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.

Census 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

Interactive analysis of estimated UK population change, by geography, age and sex. Annual estimates are for mid-2011 to mid-2016.

ArcGIS includes a comprehensive set of demographic and purchasing maps and data for dozens of countries around the world. This includes recent demographic information such as total population, family size, marital status, population by age, and more. It also includes purchasing information on many types of products. This information can be accessed as ready-to-use map layers, including pre-configured popups, which can be re-styled and added to your maps and apps. The primary source of this information is Michael Bauer Research.This map features a small selection of these map layers that are available to users with an ArcGIS Online subscription. You can preview several of the map layers in this map. To access the map layers individually, please visit the Demographics and Lifestyle group, which features a complete set of ready-to-use maps and map layers, and can be searched for maps in specific countries.

This 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.

This layer shows total population count by sex and age group. This is shown by tract, county, and state boundaries. This service 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 also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the population that are considered dependent (ages 65+ and <18). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B01001Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, 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 level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

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

This time animated interactive map shows census population statistics from 1921 to 2011 for municipalities surrounding the Strait of Georgia.

Interactive web map for Understanding World Regional Geography, 1st Edition. Fouberg, Erin H., and William G. Moseley. Understanding World Regional Geography. 1st ed. John Wiley & Sons, 2015.

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.

The world is a crowded place, with more than 7 billion people on the planet as of 2014. About half of this population lives in urban areas, and ongoing migration into city centers has given rise to the megacity—a metropolitan area with 10 million people or more. This story map was produced by Esri's story map team. It is a customization of the Esri Story Map Journal app, and was created in collaboration with the Smithsonian Institution. This story map was also published on Smithsonian.com:https://www.smithsonianmag.com/science-nature/make-cities-explode-size-these-interactive-maps-180952832/

Explore the varying population numbers in African countries with data from the United Nations. This interactive resource visualizes the distribution and trends of populations across Africa, providing a comprehensive assessment of demographic changes shaping Africa's landscape

• Population 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

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.

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