17 datasets found
  1. w

    Washington Cities by Population

    • washington-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Washington Cities by Population [Dataset]. https://www.washington-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.washington-demographics.com/terms_and_conditionshttps://www.washington-demographics.com/terms_and_conditions

    Area covered
    Tacoma, Washington
    Description

    A dataset listing Washington cities by population for 2024.

  2. i

    Iowa Cities by Population

    • iowa-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Iowa Cities by Population [Dataset]. https://www.iowa-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.iowa-demographics.com/terms_and_conditionshttps://www.iowa-demographics.com/terms_and_conditions

    Description

    A dataset listing Iowa cities by population for 2024.

  3. n

    New York Cities by Population

    • newyork-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). New York Cities by Population [Dataset]. https://www.newyork-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.newyork-demographics.com/terms_and_conditionshttps://www.newyork-demographics.com/terms_and_conditions

    Area covered
    New York
    Description

    A dataset listing New York cities by population for 2024.

  4. v

    Virginia Cities by Population

    • virginia-demographics.com
    Updated Jun 20, 2024
    + more versions
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    Kristen Carney (2024). Virginia Cities by Population [Dataset]. https://www.virginia-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.virginia-demographics.com/terms_and_conditionshttps://www.virginia-demographics.com/terms_and_conditions

    Area covered
    Virginia
    Description

    A dataset listing Virginia cities by population for 2024.

  5. g

    Georgia Cities by Population

    • georgia-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Georgia Cities by Population [Dataset]. https://www.georgia-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.georgia-demographics.com/terms_and_conditionshttps://www.georgia-demographics.com/terms_and_conditions

    Area covered
    Georgia
    Description

    A dataset listing Georgia cities by population for 2024.

  6. o

    Oregon Cities by Population

    • oregon-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Oregon Cities by Population [Dataset]. https://www.oregon-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.oregon-demographics.com/terms_and_conditionshttps://www.oregon-demographics.com/terms_and_conditions

    Area covered
    Oregon
    Description

    A dataset listing Oregon cities by population for 2024.

  7. i

    Indiana Cities by Population

    • indiana-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Indiana Cities by Population [Dataset]. https://www.indiana-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.indiana-demographics.com/terms_and_conditionshttps://www.indiana-demographics.com/terms_and_conditions

    Area covered
    Indiana
    Description

    A dataset listing Indiana cities by population for 2024.

  8. Locales 2014

    • s.cnmilf.com
    • datasets.ai
    • +4more
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). Locales 2014 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/locales-2014-81d3a
    Explore at:
    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2014 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2014. The NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.All information contained in this file is in the public _domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

  9. w

    Wisconsin Cities by Population

    • wisconsin-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Wisconsin Cities by Population [Dataset]. https://www.wisconsin-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.wisconsin-demographics.com/terms_and_conditionshttps://www.wisconsin-demographics.com/terms_and_conditions

    Area covered
    Wisconsin
    Description

    A dataset listing Wisconsin cities by population for 2024.

  10. l

    Louisiana Cities by Population

    • louisiana-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Louisiana Cities by Population [Dataset]. https://www.louisiana-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.louisiana-demographics.com/terms_and_conditionshttps://www.louisiana-demographics.com/terms_and_conditions

    Area covered
    Louisiana, Shreveport
    Description

    A dataset listing Louisiana cities by population for 2024.

  11. c

    Colorado Cities by Population

    • colorado-demographics.com
    • myaistarter.com.tubetargeterapp.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Colorado Cities by Population [Dataset]. https://www.colorado-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.colorado-demographics.com/terms_and_conditionshttps://www.colorado-demographics.com/terms_and_conditions

    Area covered
    Colorado
    Description

    A dataset listing Colorado cities by population for 2024.

  12. u

    Utah Cities by Population

    • utah-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Utah Cities by Population [Dataset]. https://www.utah-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.utah-demographics.com/terms_and_conditionshttps://www.utah-demographics.com/terms_and_conditions

    Description

    A dataset listing Utah cities by population for 2024.

  13. Data from: Urban-rural continuum

    • figshare.com
    tiff
    Updated May 30, 2023
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    Andrea Cattaneo; Andy Nelson; Theresa McMenomy (2023). Urban-rural continuum [Dataset]. http://doi.org/10.6084/m9.figshare.12579572.v4
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    tiffAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Andrea Cattaneo; Andy Nelson; Theresa McMenomy
    License

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

    Description

    The urban–rural continuum classifies the global population, allocating rural populations around differently-sized cities. The classification is based on four dimensions: population distribution, population density, urban center location, and travel time to urban centers, all of which can be mapped globally and consistently and then aggregated as administrative unit statistics.Using spatial data, we matched all rural locations to their urban center of reference based on the time needed to reach these urban centers. A hierarchy of urban centers by population size (largest to smallest) is used to determine which center is the point of “reference” for a given rural location: proximity to a larger center “dominates” over a smaller one in the same travel time category. This was done for 7 urban categories and then aggregated, for presentation purposes, into “large cities” (over 1 million people), “intermediate cities” (250,000 –1 million), and “small cities and towns” (20,000–250,000).Finally, to reflect the diversity of population density across the urban–rural continuum, we distinguished between high-density rural areas with over 1,500 inhabitants per km2 and lower density areas. Unlike traditional functional area approaches, our approach does not define urban catchment areas by using thresholds, such as proportion of people commuting; instead, these emerge endogenously from our urban hierarchy and by calculating the shortest travel time.Urban-Rural Catchment Areas (URCA).tif is a raster dataset of the 30 urban–rural continuum categories for the urban–rural continuum showing the catchment areas around cities and towns of different sizes. Each rural pixel is assigned to one defined travel time category: less than one hour, one to two hours, and two to three hours travel time to one of seven urban agglomeration sizes. The agglomerations range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people. The remaining pixels that are more than 3 hours away from any urban agglomeration of at least 20,000 people are considered as either hinterland or dispersed towns being that they are not gravitating around any urban agglomeration. The raster also allows for visualizing a simplified continuum created by grouping the seven urban agglomerations into 4 categories.Urban-Rural Catchment Areas (URCA).tif is in GeoTIFF format, band interleaved with LZW compression, suitable for use in Geographic Information Systems and statistical packages. The data type is byte, with pixel values ranging from 1 to 30. The no data value is 128. It has a spatial resolution of 30 arc seconds, which is approximately 1km at the equator. The spatial reference system (projection) is EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long). The geographic extent is 83.6N - 60S / 180E - 180W. The same tif file is also available as an ESRI ArcMap MapPackage Urban-Rural Catchment Areas.mpkFurther details are in the ReadMe_data_description.docx

  14. A

    ‘Locales 2019’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Apr 3, 2018
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2018). ‘Locales 2019’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-locales-2019-efaa/ecbe3e91/?iid=000-641&v=presentation
    Explore at:
    Dataset updated
    Apr 3, 2018
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Locales 2019’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/26ac55dc-dcbd-467f-995f-319e789dd198 on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2019 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2019. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:

    • City - Large (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.
    • City - Midsize (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.
    • City - Small (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.
    • Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.
    • Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.
    • Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.
    • Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.
    • Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.
    • Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.
    • Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.
    • Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.
    • Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.

    --- Original source retains full ownership of the source dataset ---

  15. a

    Massachusetts Gateway Cities (Feature Service)

    • hub.arcgis.com
    • gis.data.mass.gov
    • +1more
    Updated May 6, 2024
    + more versions
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    Massachusetts Gateway Cities (Feature Service) [Dataset]. https://hub.arcgis.com/datasets/dab5a7f3cfad446eaba76effd5926150
    Explore at:
    Dataset updated
    May 6, 2024
    Dataset authored and provided by
    MassGIS - Bureau of Geographic Information
    Area covered
    Description

    This map service from MassGIS displays the 26 Massachusetts Gateway Cities, municipalities with:population greater than 35,000 and less than 250,000;median household income below the state average;and rate of educational attainment of a bachelor’s degree or above that is below the state average.Read more about Gateway CitiesMap service also available.

  16. Labour indicators by access to city typology

    • db.nomics.world
    Updated Jul 1, 2025
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    DBnomics (2025). Labour indicators by access to city typology [Dataset]. https://db.nomics.world/OECD/DSD_REG_LAB@DF_TYPE_METRO
    Explore at:
    Dataset updated
    Jul 1, 2025
    Authors
    DBnomics
    Description

    This dataset provides labour market indicators aggregated at national level and broken down by territorial typology according to the population's access to cities.

    Data source and definition

    I>The indicators include labour indicators at place of residence by type of territory. Data is based on a labor force survey using ILO methodology and collected from Eurostat (reg_lmk) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites.

    The indicators are aggregated data at the national level, using the typology of small (TL3) regions to calculate totals or averages for all metropolitan large regions, metropolitan midsize regions, near a midsize/large FUA regions, near a small FUA regions and remote regions.

    Territorial typology on the population's access to cities

    Territorial typologies helps to assess differences in socio-economic trends in regions, both within and across countries and to highlight the specific issues faced by each type of region.

    The OECD territorial typology on access to cities uses the concept of functional urban areas (FUA) – composed of urban centres and their commuting areas – and classifies small (TL3) regions (Fadic et al., 2019) according to the following criteria:

    • Metropolitan regions, if more than half of the population live in a FUA. Metropolitan regions are further classified into: metropolitan large, if more than half of the population live in a (large) FUA of at least 1.5 million inhabitants; and metropolitan midsize, if more than half of the population live in a (midsize) FUA of at 250 000 to 1.5 million inhabitants.
    • Non-metropolitan regions, if less than half of the population live in a midsize/large FUA. These regions are further classified according to their level of access to FUAs of different sizes: near a midsize/large FUA if more than half of the population live within a 60-minute drive from a midsize/large FUA (of more than 250 000 inhabitants) or if the TL3 region contains more than 80% of the area of a midsize/large FUA; near a small FUA if the region does not have access to a midsize/large FUA and at least half of its population have access to a small FUA (i.e. between 50 000 and 250 000 inhabitants) within a 60-minute drive, or contains 80% of the area of a small FUA; and remote, otherwise.

    List of OECD regions and typologies are presented in the OECD Territorial correspondence table (xlsx). Maps of OECD regions are presented in the OECD Territorial grid (pdf).

    Cite this dataset

    OECD Regions and Cities databases http://oe.cd/geostats

    Further information

    Contact: RegionStat@oecd.org

  17. Global Urban Rural Catchment Areas (URCA) Grid - 2021

    • data.amerigeoss.org
    http, png, tif, wms
    Updated Mar 5, 2022
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    Food and Agriculture Organization (2022). Global Urban Rural Catchment Areas (URCA) Grid - 2021 [Dataset]. https://data.amerigeoss.org/dataset/9dc31512-a438-4b59-acfd-72830fbd6943
    Explore at:
    wms, png, http, tifAvailable download formats
    Dataset updated
    Mar 5, 2022
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

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

    Description

    The Global Urban-Rural Catchment Areas (URCA) is a raster dataset of the 30 urban-rural continuum categories of catchment areas for cities and towns. Each rural pixel is assigned to one defined travel time category: less than one hour, one to two hours, and two to three hours travel time to one of seven urban agglomeration sizes. The agglomerations range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people. The remaining pixels that are more than 3 hours away from any urban agglomeration of at least 20,000 people are considered as either hinterland or dispersed towns being that they are not gravitating around any urban agglomeration.

    Data publication: 2021-01-01

    Contact points:

    Metadata contact: Theresa McMenomy FAO-UN

    Contact: Andrea Cattaneo FAO-UN

    Contact: Theresa McMenomy FAO-UN

    Data lineage:

    The dataset is from https://doi/10.1073/pnas.2011990118 and http://dx.doi.org/10.6084/m9.figshare.12579572

    Resource constraints:

    CC By 4.0

    Online resources:

    Urban-rural continuum dataset download

    urban_rural_catchment_areas.tif

  18. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Kristen Carney (2024). Washington Cities by Population [Dataset]. https://www.washington-demographics.com/cities_by_population

Washington Cities by Population

Explore at:
Dataset updated
Jun 20, 2024
Dataset provided by
Cubit Planning, Inc.
Authors
Kristen Carney
License

https://www.washington-demographics.com/terms_and_conditionshttps://www.washington-demographics.com/terms_and_conditions

Area covered
Tacoma, Washington
Description

A dataset listing Washington cities by population for 2024.

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