65 datasets found
  1. L

    Laos LA: Population Density: Inhabitants per sq km

    • ceicdata.com
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    CEICdata.com, Laos LA: Population Density: Inhabitants per sq km [Dataset]. https://www.ceicdata.com/en/laos/social-demography-non-oecd-member-annual/la-population-density-inhabitants-per-sq-km
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    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    Laos
    Description

    Laos LA: Population Density: Inhabitants per sq km data was reported at 32.750 Person in 2022. This records an increase from the previous number of 32.290 Person for 2021. Laos LA: Population Density: Inhabitants per sq km data is updated yearly, averaging 25.840 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 32.750 Person in 2022 and a record low of 18.680 Person in 1990. Laos LA: 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 Laos – Table LA.OECD.GGI: Social: Demography: Non OECD Member: Annual.

  2. L

    Laos LA: Population Density: People per Square Km

    • ceicdata.com
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    CEICdata.com, Laos LA: Population Density: People per Square Km [Dataset]. https://www.ceicdata.com/en/laos/population-and-urbanization-statistics/la-population-density-people-per-square-km
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    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Laos
    Variables measured
    Population
    Description

    Laos LA: Population Density: People per Square Km data was reported at 29.715 Person/sq km in 2017. This records an increase from the previous number of 29.282 Person/sq km for 2016. Laos LA: Population Density: People per Square Km data is updated yearly, averaging 17.931 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 29.715 Person/sq km in 2017 and a record low of 9.404 Person/sq km in 1961. Laos LA: 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 Laos – Table LA.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;

  3. Top 20 metropolitan areas in the United States in 2013, by population...

    • statista.com
    Updated Oct 22, 2014
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    Statista (2014). Top 20 metropolitan areas in the United States in 2013, by population density [Dataset]. https://www.statista.com/statistics/431940/metropolitan-areas-in-the-united-states-by-population-density/
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    Dataset updated
    Oct 22, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2013
    Area covered
    United States
    Description

    This statistics shows a ranking of the metropolitan areas in the United States in 2013 with the highest population density. As of 2013, Los Angeles-Long Beach-Anaheim in California was ranked first with a population density of 1,046 inhabitants per square kilometer.

  4. 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.

  5. l

    Census 2020 SRR and Demographic Charcateristics

    • geohub.lacity.org
    • data.lacounty.gov
    • +2more
    Updated Dec 22, 2023
    + more versions
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    County of Los Angeles (2023). Census 2020 SRR and Demographic Charcateristics [Dataset]. https://geohub.lacity.org/maps/e137518f57cf4dbc96ac7139a224631e
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    Dataset updated
    Dec 22, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    For the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail.The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts.The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate.More information about these data is available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review FAQs.Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data.Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR).1. Population Density: 2020 Population per square mile,2. Poverty Rate: Percentage of population under 100% FPL,3. Median Household income: Based on countywide median HH income of $71,538.4. Highschool Education Attainment: Percentage of 18 years and older population without high school graduation.5. English Speaking Ability: Percentage of 18 years and older population with less or none English speaking ability. 6. Household without Internet Access: Percentage of HH without internet access.7. Non-Hispanic White Population: Percentage of Non-Hispanic White population.8. Non-Hispanic African-American Population: Percentage of Non-Hispanic African-American population.9. Non-Hispanic Asian Population: Percentage of Non-Hispanic Asian population.10. Hispanic Population: Percentage of Hispanic population.

  6. Density of population in the Parisian region 2025, by department

    • statista.com
    Updated Jun 30, 2025
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    Statista (2025). Density of population in the Parisian region 2025, by department [Dataset]. https://www.statista.com/statistics/1047176/population-density-ile-de-france-paris-region-by-department-france/
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    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    France
    Description

    This bar chart presents the estimated population density in the Ile-de-France region (Paris area), in France, in 2025, by district. It appears that the city of Paris counted approximately 19,509 inhabitants per square kilometer, making it the most densely populated department in the region.

  7. Vietnam Population Density: NM: Son La

    • ceicdata.com
    + more versions
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    CEICdata.com, Vietnam Population Density: NM: Son La [Dataset]. https://www.ceicdata.com/en/vietnam/population-density-by-provinces/population-density-nm-son-la
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Vietnam
    Variables measured
    Population
    Description

    Vietnam Population Density: NM: Son La data was reported at 93.100 Person/sq km in 2023. This records an increase from the previous number of 92.000 Person/sq km for 2022. Vietnam Population Density: NM: Son La data is updated yearly, averaging 85.900 Person/sq km from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 93.100 Person/sq km in 2023 and a record low of 78.700 Person/sq km in 2011. Vietnam Population Density: NM: Son La data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G003: Population Density: By Provinces.

  8. a

    Density of LA Transit Stops

    • gis-for-racialequity.hub.arcgis.com
    Updated Mar 1, 2017
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    ArcGIS Living Atlas Team (2017). Density of LA Transit Stops [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/d00115f976384fc3b6e0ea6b08f0e944
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    Dataset updated
    Mar 1, 2017
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map uses smart mapping to show the density of transit stops in Los Angeles, CA. The stops provide information about the surrounding population of each stop.The LA Transit Stops layer displays transit stops with the following information about the population within a 5 minute walk of each transit stop:PopulationPercent employedPercent of seniorsPercent minoritiesNumber of householdsPercent below the poverty linePoverty indexDiversity indexRaceThe layer was created using Esri's Enrich Layer tool in ArcGIS Online.

  9. TIGER/Line Shapefile, Current, State, Louisiana, Census Tract

    • catalog.data.gov
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, Current, State, Louisiana, Census Tract [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-current-state-louisiana-census-tract
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Louisiana
    Description

    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.

  10. Highest population density by country 2024

    • statista.com
    Updated Jul 21, 2025
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    Statista (2025). Highest population density by country 2024 [Dataset]. https://www.statista.com/statistics/264683/top-fifty-countries-with-the-highest-population-density/
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    Dataset updated
    Jul 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    World
    Description

    Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

  11. Brussels - Population density by neighbourhoods

    • hub.arcgis.com
    • smartcity-bc5d2-domi.opendata.arcgis.com
    • +1more
    Updated Nov 28, 2013
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    Esri BeLux Online Public Data (2013). Brussels - Population density by neighbourhoods [Dataset]. https://hub.arcgis.com/datasets/940ada254c8c4e3ab2a550caad0e1dcb
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    Dataset updated
    Nov 28, 2013
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri BeLux Online Public Data
    Area covered
    Description

    Population density by neighbourhoods 2011Densité de la population par quartiers 2011Bevolkingsdichtheid per buurten 2011Source - Bron

  12. 2020 Cartographic Boundary File (KML), 2020 Census Urban Areas for United...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Dec 14, 2023
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch (Point of Contact) (2023). 2020 Cartographic Boundary File (KML), 2020 Census Urban Areas for United States, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2020-cartographic-boundary-file-kml-2020-census-urban-areas-for-united-states-1-500000
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    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The 2020 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the urban footprint. There are 2,644 Urban Areas (UAs) in this data release with either a minimum population of 5,000 or a housing unit count of 2,000 units. Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. This file includes revisions made to the 2020 Census New Orleans, LA Urban Area where the territory originally delineated as the 2020 Census Laplace--Lutcher--Gramercy, LA Urban Area was combined with the 2020 Census New Orleans, LA Urban Area to form the current New Orleans, LA Urban Area. This file includes revisions made to the 2020 Census Atlanta, GA Urban Area and Gainesville, GA Urban Area, where some urban territory originally designated to the Gainesville, GA Urban Area was reassigned to the Atlanta, GA Urban Area.

  13. E

    Data from: Population Density Dataset for the Jazira Region of Syria

    • dtechtive.com
    • finddatagovscot.dtechtive.com
    • +2more
    xml, zip
    Updated Feb 21, 2017
    + more versions
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    University of Edinburgh (2017). Population Density Dataset for the Jazira Region of Syria [Dataset]. http://doi.org/10.7488/ds/1739
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    zip(0.0096 MB), xml(0.0055 MB)Available download formats
    Dataset updated
    Feb 21, 2017
    Dataset provided by
    University of Edinburgh
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Jazira Region, Syria, TURKEY
    Description

    This population dataset complements 13 other datasets as part of a study that compared ancient settlement patterns with modern environmental conditions in the Jazira region of Syria. This study examined settlement distribution and density patterns over the past five millennia using archaeological survey reports and French 1930s 1:200,000 scale maps to locate and map archaeological sites. An archaeological site dataset was created and compared to and modelled with soil, geology, terrain (contour), surface and subsurface hydrology and normal and dry year precipitation pattern datasets; there are also three spreadsheet datasets providing 1963 precipitation and temperature readings collected at three locations in the region. The environmental datasets were created to account for ancient and modern population subsistence activities, which comprise barley and wheat farming and livestock grazing. These environmental datasets were subsequently modelled with the archaeological site dataset, as well as, land use and population density datasets for the Jazira region. Ancient trade routes were also mapped and factored into the model, and a comparison was made to ascertain if there was a correlation between ancient and modern settlement patterns and environmental conditions; the latter influencing subsistence activities. Creation of this population dataset, derived from a 1961 census, was created to compare modern population density patterns with the distribution of ancient settlement patterns to ascertain if patterns are shared. There is a similarity between these patterns with higher concentrations of settlements and population along the banks of rivers until reaching the northern area of the Jazira where both extend across the wider landscape and away from rivers. Derived from 1:1 million scale map produced for the following report: Food and Agriculture Organization (FAO), United Nations. Etude des Ressources en Eaux Souterraines de la Jezireh Syrienne. Rome: FAO, 1966.Population map was copied to mylar and scanned to create a polygon coverage of the soil classes, which include land-use attribute information. Each polygon was labelled and attributed with population count. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-07-05 and migrated to Edinburgh DataShare on 2017-02-21.

  14. Data from: California Current Ecosystem site, station Los Angeles County, CA...

    • search.dataone.org
    • portal.edirepository.org
    Updated Mar 10, 2015
    + more versions
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    U.S. Bureau of the Census; Inter-University Consortium for Political and Social Research; EcoTrends Project (2015). California Current Ecosystem site, station Los Angeles County, CA (FIPS 6037), study of human population density in units of numberPerKilometerSquared on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F966%2F2
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    Dataset updated
    Mar 10, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    U.S. Bureau of the Census; Inter-University Consortium for Political and Social Research; EcoTrends Project
    Time period covered
    Jan 1, 1880 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    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 California Current Ecosystem (CCE) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

  15. A

    Population Density base tiles

    • data.amerigeoss.org
    • communities-amerigeoss.opendata.arcgis.com
    Updated Apr 11, 2017
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    Maps.com (2017). Population Density base tiles [Dataset]. https://data.amerigeoss.org/de/dataset/population-density-base-tiles
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    geojson, html, arcgis geoservices rest api, csvAvailable download formats
    Dataset updated
    Apr 11, 2017
    Dataset provided by
    Maps.com
    Description

    Gridded Population of the World, Version 3 (GPWv3), Future Estimates 2010 consists of estimates of human population for the year 2010 by 2.5 arc-minute grid cells.

  16. e

    Demographic indicators. Population density (inhabitants / ha) of the city of...

    • data.europa.eu
    • opendata-ajuntament.barcelona.cat
    csv
    Updated Mar 13, 2013
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    Ayuntamiento de Barcelona (2013). Demographic indicators. Population density (inhabitants / ha) of the city of Barcelona [Dataset]. https://data.europa.eu/data/datasets/https-opendata-ajuntament-barcelona-cat-data-dataset-est-densitat
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    csvAvailable download formats
    Dataset updated
    Mar 13, 2013
    Dataset authored and provided by
    Ayuntamiento de Barcelona
    License

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

    Area covered
    Barcelona
    Description

    Demographic indicators. Population density (inhabitants / ha) of the city of Barcelona

  17. k

    Population density (Savannakhet, 2015)

    • en.data.savannakhet.k4d.la
    • lo.data.savannakhet.k4d.la
    Updated Jan 14, 2021
    + more versions
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    savannakhet.K4D (2021). Population density (Savannakhet, 2015) [Dataset]. https://en.data.savannakhet.k4d.la/items/58eb4c7533884cb9819d0beec2e6ff9f
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    Dataset updated
    Jan 14, 2021
    Dataset authored and provided by
    savannakhet.K4D
    Area covered
    Description

    The population density is calculated as the village population divided by the estimated area of the villageData Source: Lao Population and Housing Census 2015Contact: Ministry of Planning and Investment, Lao Statistics Bureau, Dongnasokneua Village, Sikhottabong District, Vientiane Capital Email: lstats@lsb.gov.la ; Tel: (+85621) 214740, Fax: (+86521) 242022ຄວາມໜາແໜ້ນ ຂອງພົນລະເມືອງໄດ້ຖືກຄິດໄລ່ເປັນປະຊາກອນຂອງບ້ານແບ່ງອອກຕາມພື້ນທີ່ປະມານຂອງບ້ານການສຳຫລວດສຳມະໂນປະຊາກອນ 2015ກະຊວງແຜນການ ແລະ ການລົງທຶນ, ສູນສະຖິຕິແຫ່ງຊາດ ບ້ານດົງນາໂຊກເໜືອ, ເມືອງສີໂຄດຕະບອງ, ແຂວງນະຄອນຫລວງວຽງຈັນ. ໂທ: (+856 21)214740, ແຟັກ: (+856 21)242022. ອີເມລວ: lstats@lsb.gov.la

  18. f

    Data from: Modelling population density over time: how spatial distance...

    • tandf.figshare.com
    pdf
    Updated Jun 1, 2023
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    Ilenia Epifani; Rosella Nicolini (2023). Modelling population density over time: how spatial distance matters [Dataset]. http://doi.org/10.6084/m9.figshare.3692187.v1
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Ilenia Epifani; Rosella Nicolini
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    Modelling population density over time: how spatial distance matters. Regional Studies. This study provides an empirical application of the Bayesian approach for modelling the evolution of population density distribution across time. It focuses on the case of Massachusetts by tracking changes in the importance of spatial distance from Boston concerning citizens’ choices of residence according to data for 1880–90 and 1930–2010. By adopting a Bayesian strategy, results show that Boston reinforced its attractiveness until the 1960s, when the city's accessibility no longer represented the unique determinant of population density distribution. Referring to selected historical evidence, a few possible interpretations are presented to endorse these results.

  19. k

    Population density (Persons/km2) (Laos, 2005)

    • en.data.k4d.la
    • lo.data.k4d.la
    Updated Aug 30, 2021
    + more versions
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    decide.K4D (2021). Population density (Persons/km2) (Laos, 2005) [Dataset]. https://en.data.k4d.la/items/8f0cb758ae0e406981a3c11ae1403013
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    Dataset updated
    Aug 30, 2021
    Dataset authored and provided by
    decide.K4D
    Area covered
    Description

    Population density (Persons/km2)Data Source: Lao Population and Housing Census 2005Contact: Ministry of Planning and Investment, Lao Statistics Bureau, Dongnasokneua Village, Sikhottabong District, Vientiane Capital Email: lstats@lsb.gov.la ; Tel: (+85621) 214740, Fax: (+86521) 242025ຄວາມໜາແໜ້ນຂອງພົນລະເມືອງການສຳຫລວດສຳມະໂນປະຊາກອນ 2005ກະຊວງແຜນການ ແລະ ການລົງທຶນ ສູນສະຖິຕິແຫ່ງຊາດ ບ້ານດົງນາໂຊກເໜືອ, ເມືອງສີໂຄດຕະບອງ, ແຂວງນະຄອນຫລວງວຽງຈັນ. ໂທ: (+856 21)214740, ແຟັກ: (+856 21)242022. ອີເມລວ: lstats@lsb.gov.la

  20. p

    Population density 2021

    • data.public.lu
    • geocatalogue-staging.geoportail.lu
    • +1more
    bin, wms, zip
    Updated Mar 30, 2023
    + more versions
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    SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire (2023). Population density 2021 [Dataset]. https://data.public.lu/en/datasets/population-density-2021/
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    wms, zip(959259), bin(3647298)Available download formats
    Dataset updated
    Mar 30, 2023
    Dataset authored and provided by
    SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire
    License

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

    Description

    Population density 2021 (inhabitants per km²), Lorraine: 2019 Territorial entities: arrondissements (Lorraine, Wallonie), cantons (Luxembourg), Kreise (Saarland, Rheinland-Pfalz) Statistical data sources: Destatis, INSEE, Statbel, STATEC. Harmonization: IBA / OIE 2022 Geodata sources: GeoBasis-DE / BKG 2017, IGN France 2017, NGI-Belgium 2017, ACT Luxembourg 2017. Harmonization: SIG-GR / GIS-GR 2022

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CEICdata.com, Laos LA: Population Density: Inhabitants per sq km [Dataset]. https://www.ceicdata.com/en/laos/social-demography-non-oecd-member-annual/la-population-density-inhabitants-per-sq-km

Laos LA: Population Density: Inhabitants per sq km

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Dataset provided by
CEICdata.com
License

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

Time period covered
Dec 1, 2011 - Dec 1, 2022
Area covered
Laos
Description

Laos LA: Population Density: Inhabitants per sq km data was reported at 32.750 Person in 2022. This records an increase from the previous number of 32.290 Person for 2021. Laos LA: Population Density: Inhabitants per sq km data is updated yearly, averaging 25.840 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 32.750 Person in 2022 and a record low of 18.680 Person in 1990. Laos LA: 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 Laos – Table LA.OECD.GGI: Social: Demography: Non OECD Member: Annual.

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