Mongolia MN: Population Density: Inhabitants per sq km data was reported at 2.170 Person in 2022. This records an increase from the previous number of 2.140 Person for 2021. Mongolia MN: Population Density: Inhabitants per sq km data is updated yearly, averaging 1.660 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 2.170 Person in 2022 and a record low of 1.400 Person in 1990. Mongolia MN: Population Density: Inhabitants per sq km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Mongolia – Table MN.OECD.GGI: Social: Demography: Non OECD Member: Annual.

Geospatial Analysis of Population Demographics and Traffic Density in MinneapolisIntroductionThis interactive web map provides a geospatial analysis of population distribution and traffic density for the city of Minneapolis, Minnesota. By integrating demographic data at the census tract level with real-time traffic information, the application serves as a critical tool for urban planning, transportation management, and sociological research.Data Visualization and SymbologyThe map employs distinct color schemes to represent the core datasets, allowing for intuitive visual analysis: Traffic Density: The city's road network is symbolized using a color gradient to indicate traffic volume. Segments rendered in deep red represent a high traffic density index, signifying areas of significant vehicular congestion. This transitions to a light yellow for segments experiencing lower traffic flow. Population Density: The demographic landscape is visualized using a green color ramp applied to census tract polygons. Dark green shades correspond to areas with a high population concentration, whereas lighter green shades denote regions with a lower population density. Analytical Utility and ApplicationsThe juxtaposition of these datasets reveals spatial correlations between residential density and transportation bottlenecks. This allows for data-driven inquiry into key urban challenges. The patterns visualized can help city planners and transportation authorities identify specific corridors where infrastructure investment could be most effective. Strategic improvements in these areas have the potential to optimize traffic flow, reduce commuter travel times, and decrease vehicle fuel consumption and emissions, thereby enhancing the overall sustainability and livability of Minneapolis.Interactive Features and Data ExplorationUsers are encouraged to engage with the map's interactive features for a deeper understanding of the data: Layers and Legend: Utilize the "Layers" and "Legend" tools to deconstruct the map's composition and understand the specific values associated with the color symbology. Pop-up Information: Click on individual census tracts or road segments to activate pop-up windows. These provide detailed attribute information, such as total population counts, demographic breakdowns, household income statistics, and spatial relationship metrics like nearest neighbor analysis. This application is built upon a foundational demographic data layer for Minneapolis and is enhanced by the integration of a dynamic traffic layer from the ArcGIS Living Atlas of the World.

Mongolia MN: Population Density: People per Square Km data was reported at 1.980 Person/sq km in 2017. This records an increase from the previous number of 1.949 Person/sq km for 2016. Mongolia MN: Population Density: People per Square Km data is updated yearly, averaging 1.378 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 1.980 Person/sq km in 2017 and a record low of 0.632 Person/sq km in 1961. Mongolia MN: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mongolia – Table MN.World Bank: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted Average;

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Cedar Creek Ecosystem Science Reserve (CDR) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Marcell Experimental Forest (MAR) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

The Census Bureau has completed the delineation of the Census 2000 urbanized areas (UA) and urban clusters (UC). The Census Bureau identifies and tabulates data for the urban and rural populations and their associated areas solely for the presentation and comparison of census statistical data. For Census 2000, the Census Bureau classifies as urban all territory, population, and housing units located within an urbanized area (UA) or an urban cluster (UC). It delineates UA and UC boundaries to encompass densely settled territory, which consists of:

- core census block groups or blocks that have a population density of at least 1,000 people per square mile and

- surrounding census blocks that have an overall density of at least 500 people per square mile

In addition, under certain conditions, less densely settled territory may be part of each UA or UC.

The Census Bureau's classification of rural consists of all territory, population, and housing units located outside of UAs and UCs.

For more information about the 2000 Urbanized Area please go to:
https://www.census.gov/geo/maps-data/maps/ua2kmaps.html

Population Density data was reported at 2.000 Person/sq km in 2017. This stayed constant from the previous number of 2.000 Person/sq km for 2016. Population Density data is updated yearly, averaging 1.670 Person/sq km from Dec 1963 (Median) to 2017, with 24 observations. The data reached an all-time high of 2.000 Person/sq km in 2017 and a record low of 0.700 Person/sq km in 1963. Population Density data remains active status in CEIC and is reported by Agency of Land Administration and Management, Geodesy and Cartography. The data is categorized under Global Database’s Mongolia – Table MN.G002: Population Density.

The Census Bureau has completed the delineation of the Census 2020 urban areas (UA) and urban clusters (UC). The Census Bureau identifies and tabulates data for the urban and rural populations and their associated areas solely for the presentation and comparison of census statistical data. For Census 2020, the Census Bureau classifies as urban all territory, population, and housing units located within an urban area (UA) or an urban cluster (UC). It delineates UA and UC boundaries to encompass densely settled territory, which consists of:

- core census block groups or blocks that have a population density of at least 1,000 people per square mile and

- surrounding census blocks that have an overall density of at least 500 people per square mile

In addition, under certain conditions, less densely settled territory may be part of each UA or UC.

The Census Bureau's classification of rural consists of all territory, population, and housing units located outside of UAs and UCs.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Cedar Creek Ecosystem Science Reserve (CDR) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

百万：人口密度：每平方公里人口在12-01-2017达1.980Person/sq km，相较于12-01-2016的1.949Person/sq km有所增长。百万：人口密度：每平方公里人口数据按年更新，12-01-1961至12-01-2017期间平均值为1.378Person/sq km，共57份观测结果。该数据的历史最高值出现于12-01-2017，达1.980Person/sq km，而历史最低值则出现于12-01-1961，为0.632Person/sq km。CEIC提供的百万：人口密度：每平方公里人口数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的蒙古 – 表 MN.世界银行：人口和城市化进程统计。

This dataset contains remotely sensed estimates of nitrogen dioxide (NO2, via TROPOMI accessed via Google Earth Engine) for HOLC neighborhoods in 11 US Midwestern cities, and corresponding coarse geographic and demographic data of those cities. NO2 data is reported daily for the entire calendar year of 2019, geographic and demographic variables are fixed for each city for the entire year. Each HOLC-graded neighborhood included in this dataset was filtered to be greater than 2 km2. The number of pixels used to calculate the area-weighted mean of NO2 is also reported, as is the area of the neighborhood. The dataset has also been filtered for observations that did not pass quality filters for L3 TROPOMI data. The cities included in the study are: Chicago IL, Milwaukee WI, Saint Paul MN, Minneapolis MN, Indianapolis IN, Cleveland OH, Wichita KS, Greater Kansas City KS and MO, Columbus OH, Detroit MI, and Omaha NE. HOLC neighborhood shapefiles were obtained from the Mapping Inequality project website, hosted by the University of Richmond, and resulting polygons used in analysis were created by dissolving shared boundaries in Google Earth Engine. City populations and population density were obtained from the US 2010 Census data. All data was collected and organized to assess if current day NO2 levels varied with HOLC grades in these major cities.

Data was used in the study: Hrycyna et al. (2022) Elementa 10(1):00027

Robert K. Nelson, LaDale Winling, Richard Marciano, Nathan Connolly, et al., “Mapping Inequality,” American Panorama, ed. https://dsl.richmond.edu/panorama/redlining/#loc=5/39.1/-94.58&text=downloads

Dataset for all analyses presented in Hrycyna et al. Columns described below:

HOLC_grade: A, B, C, D (neighborhood grade categories obtained from Mapping Inequality project, indicate historic HOLC designations of neighborhoods).

HOLCAreaKm2: continuous area value in km2 of the HOLC neighborhood polygon, which may be more than one HOLC designated polygon merged from the shapefiles downloaded from Mapping Inequality.

pixelcount: integer values of the number of TROPOMI NO2 pixels used to produce the area-weighted mean NO2 value.

NO2_mol_m2: area-weighted mean value of TROPOMI NO2 for that HOLC neighborhood polygon in mol m-2

system.index: designated date and time boundary of the observation collected via TROPOMI

date: date of observation

month: month of observation

City: city in the US Midwest

State: state for the city of focus

Population: urban population obtained from 2010 census

PopDensity: urban population density obtained from 2010 census, based on modern city boundaries (in people per square miles)

CityArea_mi2: Area of the city of interest, in square miles.

ln_NO2: natural log transformed NO2 values in mol m-2

NO2_DU: NO2 value converted from mol m-2 to DU (Dobsons Units, converted by multiplying 2241.15)

NO2_lnDU: natural log transformed NO2 values in DU

New York, NY, Toronto, CA-ON, and San Franscisco, CA were the most pedestrian friendly cities in the United States in 2021. The source analyzed the walking routes of different locations in the 50 largest cities in the country to different amenities, as well as additional metrics, such as population density, block length, and intersection density. New York, NY received 88.6 index points, while the 20th city in the ranking, Minneapolis, MN, received 55 index points.

As of year 2024, the population of Mumbai, India was over **** million inhabitants. This was a **** percent growth from last year. The historical trends indicate that the population of Mumbai has been steadily increasing since 1960. The UN estimates that the population is expected to reach over ** million by the year 2030.