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 whiteThe 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.)

Web Map Service that supports the IRENA Global Atlas for Renewable EnergyThe LandScan 2018 Global Population Database was developed by Oak Ridge National Laboratory (ORNL) for the United States Department of Defense (DoD).ORNL’s LandScan™ is a community standard for global population distribution data. At approximately 1 km (30″ X 30″) spatial resolution, it represents an ambient population (average over 24 hours) distribution. The database is refreshed annually and released to the broader user community around October. LandScan™ is now available at no cost to the educational community. The latest LandScan™ dataset available is LandScan Global 2018. Older LandScan Global data sets (LandScan 1998, 2000-2017) are available through site. These data set can be licensed for commercial and other applications through multiple third-party vendors. LandScan is developed using best available demographic (Census) and geographic data, remote sensing imagery analysis techniques within a multivariate dasymetric modeling framework to disaggregate census counts within an administrative boundary. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution is essentially a combination of locally adoptive models that are tailored to match the data conditions and geographical nature of each individual country and region.

The Kresge early childhood interactive map contains data relating to early childhood and education. It is meant to help stakeholders better understand the early childhood landscape better.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Georgia data available from WorldPop here.

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).

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

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

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.

A custom basemap created for internal Connecticut Department of Transportation in web apps and maps.The basemap represents the most recent and active Public Road Network as maintained by the Bureau of Policy & Planning's Roadway Inventory Unit and is updated on an annual basis.Map styling mimics the format of an Open Street Maps style basemap and routes are differentiated by their prefix (e.g. Interstate, US, CT, etc.) with local roads sharing the same symbiology across the state.At closer zoom levels, ortho imagery from 2023 (provided by CTECO) appears within the map extent.Pop-ups are configured to show route information after selection, including LRS Route ID, Town, Primary/Secondary Route Designation, Segment Milepoint Extents, Route Type, etc.).

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The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Armenia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

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.

This map displays the change in population from 2014 to 2045 based from census data. The population projections for Genesee County were produced on a traffic analysis zone (TAZ) level where growth/decline was calculated for each TAZ which can then be aggregated up to the municipality level for all cities, townships and some villages. Genesee County is divided into 639 TAZ. The distribution of population and housing from the 2010 Census redistricting data was used to populate the 2014 TAZ with 2014 Census estimate data. 2014 Census estimates were used to calibrate 2014 base year population and housing data.

Population data for a selection of countries, allocated to 1 arcsecond blocks and provided in a combination of CSV and Cloud-optimized GeoTIFF files. This refines CIESIN’s Gridded Population of the World using machine learning models on high-resolution worldwide Maxar satellite imagery. CIESIN population counts aggregated from worldwide census data are allocated to blocks where imagery appears to contain buildings.

Auxiliary Data.gdb: Land_use: original land use data POI_name: interests-point-data from the Amap platform (name indicates category)

New_gridded_population_dataset(.gdb): experimental result data, i.e., a gridded population map of mainland China with a resolution of 100 meters

New_minus_WorldPop_PopulationResidual(.gdb): pixel-level residuals of the new gridded population dataset with the Worldpop dataset

POI_Correlation_Coefficient: Zonal statistical output of POI kernel density values: summary of various POI kernel densities in residential areas of administrative units Summary of POI Pearson correlation coefficients: sum of Pearson's correlation coefficients for 13 types of POIs at a certain bandwidth

PopulationData_AdministrativeUnitLevel.gdb: Population_data_mainlandChina_level3: population data at the district and county level in mainland China Population_data_Name_level4_Table: township and street-level population data for provinces and municipalities

Note: Due to the storage space limitation, 3D building, nighttime light, and WorldPop datasets have not been uploaded. To access these publicly available data, please visit the official website via the "Related links" at the bottom. In addition, we are not authorized to share data for the fourth level of administrative boundaries, so we only share the corresponding population data in tabular form.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Lithuania: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Tonga: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Pakistan data available from WorldPop here.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Laos data available from WorldPop here.

Source: U.S. Census Bureau, PL 94-171 Redistricting data, 2000 and 2010. Note: Census numbers for the cities of Burien and Kent do not include annexations that took place after March 31, 2010. These annexations would increase Burien to 48,072, Kent to 118,565, and decrease uninc King County to 284,089.