80 datasets found
  1. Top 20 metropolitan areas in the United States in 2010, by land area

    • statista.com
    Updated Feb 24, 2016
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    Statista (2016). Top 20 metropolitan areas in the United States in 2010, by land area [Dataset]. https://www.statista.com/statistics/431912/top-20-metropolitan-areas-in-the-united-states-by-land-area/
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    Dataset updated
    Feb 24, 2016
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2010
    Area covered
    United States
    Description

    This statistics shows a list of the top 20 largest-metropolitan areas in the United States in 2010, by land area. Riverside-San Bernardino-Ontario in California was ranked first enclosing an area of 70,612 square kilometers.

  2. Number of U.S. cities, towns, villages by population size 2019

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Number of U.S. cities, towns, villages by population size 2019 [Dataset]. https://www.statista.com/statistics/241695/number-of-us-cities-towns-villages-by-population-size/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    How many incorporated places are registered in the U.S.?

    There were 19,502 incorporated places registered in the United States as of July 31, 2019. 16,410 had a population under 10,000 while, in contrast, only 10 cities had a population of one million or more.

    Small-town America

    Suffice it to say, almost nothing is more idealized in the American imagination than small-town America. When asked where they would prefer to live, 30 percent of Americans reported that they would prefer to live in a small town. Americans tend to prefer small-town living due to a perceived slower pace of life, close-knit communities, and a more affordable cost of living when compared to large cities.

    An increasing population

    Despite a preference for small-town life, metropolitan areas in the U.S. still see high population figures, with the New York, Los Angeles, and Chicago metro areas being the most populous in the country. Metro and state populations are projected to increase by 2040, so while some may move to small towns to escape city living, those small towns may become more crowded in the upcoming decades.

  3. Most populated U.S. cities in 2022

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Most populated U.S. cities in 2022 [Dataset]. https://www.statista.com/statistics/205589/top-20-cities-in-the-us-with-the-highest-resident-population/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows the top 25 cities in the United States with the highest resident population as of July 1, 2022. There were about 8.34 million people living in New York City as of July 2022.

  4. United States US: Population in Largest City: as % of Urban Population

    • ceicdata.com
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    CEICdata.com, United States US: Population in Largest City: as % of Urban Population [Dataset]. https://www.ceicdata.com/en/united-states/population-and-urbanization-statistics/us-population-in-largest-city-as--of-urban-population
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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, 2005 - Dec 1, 2016
    Area covered
    United States
    Variables measured
    Population
    Description

    United States US: Population in Largest City: as % of Urban Population data was reported at 7.020 % in 2017. This records a decrease from the previous number of 7.065 % for 2016. United States US: Population in Largest City: as % of Urban Population data is updated yearly, averaging 8.675 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 11.200 % in 1960 and a record low of 7.020 % in 2017. United States US: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

  5. Data from: Spatial-temporal change of climate in relation to urban fringe...

    • search.dataone.org
    • portal.edirepository.org
    Updated Oct 4, 2013
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    Anthony Brazel; Brent Hedquist (2013). Spatial-temporal change of climate in relation to urban fringe development in central Arizona-Phoenix [Dataset]. https://search.dataone.org/view/knb-lter-cap.34.9
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    Dataset updated
    Oct 4, 2013
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Anthony Brazel; Brent Hedquist
    Time period covered
    Aug 18, 2001 - May 1, 2002
    Area covered
    Variables measured
    RH, id, MAX, MIN, STD, SUM, AREA, Date, MEAN, time, and 8 more
    Description

    Not many studies have documented climate and air quality changes of settlements at early stages of development. This is because high quality climate and air quality records are deficient for the periods of the early 18th century to mid 20th century when many U.S. cities were formed and grew. Dramatic landscape change induces substantial local climate change during the incipient stage of development. Rapid growth along the urban fringe in Phoenix, coupled with a fine-grained climate monitoring system, provide a unique opportunity to study the climate impacts of urban development as it unfolds. Generally, heat islands form, particularly at night, in proportion to city population size and morphological characteristics. Drier air is produced by replacement of the countryside's moist landscapes with dry, hot urbanized surfaces. Wind is increased due to turbulence induced by the built-up urban fabric and its morphology; although, depending on spatial densities of buildings on the land, wind may also decrease. Air quality conditions are worsened due to increased city emissions and surface disturbances. Depending on the diversity of microclimates in pre-existing rural landscapes and the land-use mosaic in cities, the introduction of settlements over time and space can increase or decrease the variety of microclimates within and near urban regions. These differences in microclimatic conditions can influence variations in health, ecological, architectural, economic, energy and water resources, and quality-of-life conditions in the city. Therefore, studying microclimatic conditions which change in the urban fringe over time and space is at the core of urban ecological goals as part of LTER aims. In analyzing Phoenix and Baltimore long-term rural/urban weather and climate stations, Brazel et al. (In progress) have discovered that long-term (i.e., 100 years) temperature changes do not correlate with populations changes in a linear manner, but rather in a third-order nonlinear response fashion. This nonlinear temporal change is consistent with the theories in boundary layer climatology that describe and explain the leading edge transition and energy balance theory. This pattern of urban vs. rural temperature response has been demonstrated in relation to spatial range of city sizes (using population data) for 305 rural vs. urban climate stations in the U.S. Our recent work on the two urban LTER sites has shown that a similar climate response pattern also occurs over time for climate stations that were initially located in rural locations have been overrun bu the urban fringe and subsequent urbanization (e.g., stations in Baltimore, Mesa, Phoenix, and Tempe). Lack of substantial numbers of weather and climate stations in cities has previously precluded small-scale analyses of geographic variations of urban climate, and the links to land-use change processes. With the advent of automated weather and climate station networks, remote-sensing technology, land-use history, and the focus on urban ecology, researchers can now analyze local climate responses as a function of the details of land-use change. Therefore, the basic research question of this study is: How does urban climate change over time and space at the place of maximum disturbance on the urban fringe? Hypotheses 1. Based on the leading edge theory of boundary layer climate change, largest changes should occur during the period of peak development of the land when land is being rapidly transformed from open desert and agriculture to residential, commercial, and industrial uses. 2. One would expect to observe, on average and on a temporal basis (several years), nonlinear temperature and humidity alterations across the station network at varying levels of urban development. 3. Based on past research on urban climate, one would expect to see in areas of the urban fringe, rapid changes in temperature (increases at night particularly), humidity (decreases in areas from agriculture to urban; increases from desert to urban), and wind speed (increases due to urban heating). 4. Changes of the surface climate on the urban fringe are expected to be altered as a function of various energy, moisture, and momentum control parameters, such as albedo, surface moisture, aerodynamic surface roughness, and thermal admittance. These parameters relate directly to population and land-use change (Lougeay et al. 1996).

  6. N

    cities in Dillingham Census Area Ranked by Non-Hispanic Native American...

    • neilsberg.com
    csv, json
    Updated Feb 11, 2025
    + more versions
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    Neilsberg Research (2025). cities in Dillingham Census Area Ranked by Non-Hispanic Native American Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/cities-in-dillingham-census-area-ak-by-non-hispanic-native-american-population/
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    json, csvAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Dillingham Census Area
    Variables measured
    Non-Hispanic Native American Population, Non-Hispanic Native American Population as Percent of Total Population of cities in Dillingham Census Area, AK, Non-Hispanic Native American Population as Percent of Total Non-Hispanic Native American Population of Dillingham Census Area, AK
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    This list ranks the 7 cities in the Dillingham Census Area, AK by Non-Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

    • 2019-2023 American Community Survey 5-Year Estimates
    • 2018-2022 American Community Survey 5-Year Estimates
    • 2017-2021 American Community Survey 5-Year Estimates
    • 2016-2020 American Community Survey 5-Year Estimates
    • 2015-2019 American Community Survey 5-Year Estimates

    Variables / Data Columns

    • Rank by Non-Hispanic Native American Population: This column displays the rank of cities in the Dillingham Census Area, AK by their Non-Hispanic American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
    • cities: The cities for which the rank is shown in the previous column.
    • Non-Hispanic Native American Population: The Non-Hispanic Native American population of the cities is shown in this column.
    • % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total Dillingham Census Area Non-Hispanic Native American Population: This tells us how much of the entire Dillingham Census Area, AK Non-Hispanic Native American population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  7. K

    US Major Cities

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Aug 30, 2018
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    US Department of Agriculture (USDA) (2018). US Major Cities [Dataset]. https://koordinates.com/layer/11897-us-major-cities/
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    csv, mapinfo tab, geodatabase, pdf, geopackage / sqlite, mapinfo mif, kml, shapefile, dwgAvailable download formats
    Dataset updated
    Aug 30, 2018
    Dataset authored and provided by
    US Department of Agriculture (USDA)
    Area covered
    Description

    This layer is a component of 2007_NAIP_COVERAGE_3.mxd.

  8. Largest megacities worldwide 2023, by land area

    • statista.com
    Updated May 28, 2025
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    Statista (2025). Largest megacities worldwide 2023, by land area [Dataset]. https://www.statista.com/statistics/912442/land-area-of-megacities-worldwide/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    In 2023, New York led the ranking of the largest built-up urban areas worldwide, with a land area of ****** square kilometers. Boston-Providence and Tokyo-Yokohama were the second and third largest megacities globally that year.

  9. T

    Vital Signs: Population – by city

    • data.bayareametro.gov
    Updated Oct 16, 2019
    + more versions
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    California Department of Finance (2019). Vital Signs: Population – by city [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Population-by-city/2jwr-z36f
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    application/rssxml, tsv, csv, application/rdfxml, xml, kmz, application/geo+json, kmlAvailable download formats
    Dataset updated
    Oct 16, 2019
    Dataset authored and provided by
    California Department of Finance
    Description

    VITAL SIGNS INDICATOR Population (LU1)

    FULL MEASURE NAME Population estimates

    LAST UPDATED October 2019

    DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

    DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

    California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

    U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

    U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

    U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

    Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

    Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

    Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

    The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

  10. n

    A dataset of 5 million city trees from 63 US cities: species, location,...

    • data.niaid.nih.gov
    • search.dataone.org
    • +2more
    zip
    Updated Aug 31, 2022
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    Dakota McCoy; Benjamin Goulet-Scott; Weilin Meng; Bulent Atahan; Hana Kiros; Misako Nishino; John Kartesz (2022). A dataset of 5 million city trees from 63 US cities: species, location, nativity status, health, and more. [Dataset]. http://doi.org/10.5061/dryad.2jm63xsrf
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    zipAvailable download formats
    Dataset updated
    Aug 31, 2022
    Dataset provided by
    The Biota of North America Program (BONAP)
    Cornell University
    Harvard University
    Worcester Polytechnic Institute
    Stanford University
    Authors
    Dakota McCoy; Benjamin Goulet-Scott; Weilin Meng; Bulent Atahan; Hana Kiros; Misako Nishino; John Kartesz
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    United States
    Description

    Sustainable cities depend on urban forests. City trees -- a pillar of urban forests -- improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=5,660,237 trees from 63 of the largest US cities. The data comes from tree inventories conducted at the level of cities and/or neighborhoods. Each data sheet includes detailed information on tree location, species, nativity status (whether a tree species is naturally occurring or introduced), health, size, whether it is in a park or urban area, and more (comprising 28 standardized columns per datasheet). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems. Methods See eLife manuscript for full details. Below, we provide a summary of how the dataset was collected and processed.

    Data Acquisition We limited our search to the 150 largest cities in the USA (by census population). To acquire raw data on street tree communities, we used a search protocol on both Google and Google Datasets Search (https://datasetsearch.research.google.com/). We first searched the city name plus each of the following: street trees, city trees, tree inventory, urban forest, and urban canopy (all combinations totaled 20 searches per city, 10 each in Google and Google Datasets Search). We then read the first page of google results and the top 20 results from Google Datasets Search. If the same named city in the wrong state appeared in the results, we redid the 20 searches adding the state name. If no data were found, we contacted a relevant state official via email or phone with an inquiry about their street tree inventory. Datasheets were received and transformed to .csv format (if they were not already in that format). We received data on street trees from 64 cities. One city, El Paso, had data only in summary format and was therefore excluded from analyses.

    Data Cleaning All code used is in the zipped folder Data S5 in the eLife publication. Before cleaning the data, we ensured that all reported trees for each city were located within the greater metropolitan area of the city (for certain inventories, many suburbs were reported - some within the greater metropolitan area, others not). First, we renamed all columns in the received .csv sheets, referring to the metadata and according to our standardized definitions (Table S4). To harmonize tree health and condition data across different cities, we inspected metadata from the tree inventories and converted all numeric scores to a descriptive scale including “excellent,” “good”, “fair”, “poor”, “dead”, and “dead/dying”. Some cities included only three points on this scale (e.g., “good”, “poor”, “dead/dying”) while others included five (e.g., “excellent,” “good”, “fair”, “poor”, “dead”). Second, we used pandas in Python (W. McKinney & Others, 2011) to correct typos, non-ASCII characters, variable spellings, date format, units used (we converted all units to metric), address issues, and common name format. In some cases, units were not specified for tree diameter at breast height (DBH) and tree height; we determined the units based on typical sizes for trees of a particular species. Wherever diameter was reported, we assumed it was DBH. We standardized health and condition data across cities, preserving the highest granularity available for each city. For our analysis, we converted this variable to a binary (see section Condition and Health). We created a column called “location_type” to label whether a given tree was growing in the built environment or in green space. All of the changes we made, and decision points, are preserved in Data S9. Third, we checked the scientific names reported using gnr_resolve in the R library taxize (Chamberlain & Szöcs, 2013), with the option Best_match_only set to TRUE (Data S9). Through an iterative process, we manually checked the results and corrected typos in the scientific names until all names were either a perfect match (n=1771 species) or partial match with threshold greater than 0.75 (n=453 species). BGS manually reviewed all partial matches to ensure that they were the correct species name, and then we programmatically corrected these partial matches (for example, Magnolia grandifolia-- which is not a species name of a known tree-- was corrected to Magnolia grandiflora, and Pheonix canariensus was corrected to its proper spelling of Phoenix canariensis). Because many of these tree inventories were crowd-sourced or generated in part through citizen science, such typos and misspellings are to be expected. Some tree inventories reported species by common names only. Therefore, our fourth step in data cleaning was to convert common names to scientific names. We generated a lookup table by summarizing all pairings of common and scientific names in the inventories for which both were reported. We manually reviewed the common to scientific name pairings, confirming that all were correct. Then we programmatically assigned scientific names to all common names (Data S9). Fifth, we assigned native status to each tree through reference to the Biota of North America Project (Kartesz, 2018), which has collected data on all native and non-native species occurrences throughout the US states. Specifically, we determined whether each tree species in a given city was native to that state, not native to that state, or that we did not have enough information to determine nativity (for cases where only the genus was known). Sixth, some cities reported only the street address but not latitude and longitude. For these cities, we used the OpenCageGeocoder (https://opencagedata.com/) to convert addresses to latitude and longitude coordinates (Data S9). OpenCageGeocoder leverages open data and is used by many academic institutions (see https://opencagedata.com/solutions/academia). Seventh, we trimmed each city dataset to include only the standardized columns we identified in Table S4. After each stage of data cleaning, we performed manual spot checking to identify any issues.

  11. o

    Counties - United States of America

    • public.opendatasoft.com
    • bfortune.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 6, 2024
    + more versions
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    (2024). Counties - United States of America [Dataset]. https://public.opendatasoft.com/explore/dataset/georef-united-states-of-america-county/
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    excel, json, geojson, csvAvailable download formats
    Dataset updated
    Jun 6, 2024
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

  12. Locales 2017

    • s.cnmilf.com
    • catalog.data.gov
    • +2more
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). Locales 2017 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/locales-2017-c0db1
    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 2017 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2017. 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: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.

  13. Cities with the largest share of parkland in the U.S. 2023

    • statista.com
    Updated Jun 24, 2024
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    Statista (2024). Cities with the largest share of parkland in the U.S. 2023 [Dataset]. https://www.statista.com/statistics/189711/parkland-as-percentage-of-city-area-in-the-us-2009/
    Explore at:
    Dataset updated
    Jun 24, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the city in the United States with the highest share of parkland was Anchorage, Alaska, where approximately 80 percent of the city was parkland. In second place, with almost half the percentage of parkland was Fremont, California, where 44 percent of the city was parkland.

  14. 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.

  15. 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.

  16. N

    cities in Aleutians West Census Area Ranked by Hispanic Black Population //...

    • neilsberg.com
    csv, json
    Updated Feb 11, 2025
    + more versions
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    Neilsberg Research (2025). cities in Aleutians West Census Area Ranked by Hispanic Black Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/cities-in-aleutians-west-census-area-ak-by-hispanic-black-population/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Aleutians West Census Area
    Variables measured
    Hispanic Black Population, Hispanic Black Population as Percent of Total Population of cities in Aleutians West Census Area, AK, Hispanic Black Population as Percent of Total Hispanic Black Population of Aleutians West Census Area, AK
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    This list ranks the 5 cities in the Aleutians West Census Area, AK by Hispanic Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

    • 2019-2023 American Community Survey 5-Year Estimates
    • 2018-2022 American Community Survey 5-Year Estimates
    • 2017-2021 American Community Survey 5-Year Estimates
    • 2016-2020 American Community Survey 5-Year Estimates
    • 2015-2019 American Community Survey 5-Year Estimates

    Variables / Data Columns

    • Rank by Hispanic Black Population: This column displays the rank of cities in the Aleutians West Census Area, AK by their Hispanic Black or African American population, using the most recent ACS data available.
    • cities: The cities for which the rank is shown in the previous column.
    • Hispanic Black Population: The Hispanic Black population of the cities is shown in this column.
    • % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Black. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total Aleutians West Census Area Hispanic Black Population: This tells us how much of the entire Aleutians West Census Area, AK Hispanic Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  17. 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
    Shreveport, Louisiana
    Description

    A dataset listing Louisiana cities by population for 2024.

  18. N

    cities in Bethel Census Area Ranked by Non-Hispanic Black Population // 2025...

    • neilsberg.com
    csv, json
    Updated Feb 11, 2025
    + more versions
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    Neilsberg Research (2025). cities in Bethel Census Area Ranked by Non-Hispanic Black Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/cities-in-bethel-census-area-ak-by-non-hispanic-black-population/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Bethel Census Area
    Variables measured
    Non-Hispanic Black Population, Non-Hispanic Black Population as Percent of Total Population of cities in Bethel Census Area, AK, Non-Hispanic Black Population as Percent of Total Non-Hispanic Black Population of Bethel Census Area, AK
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    This list ranks the 18 cities in the Bethel Census Area, AK by Non-Hispanic Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

    • 2019-2023 American Community Survey 5-Year Estimates
    • 2018-2022 American Community Survey 5-Year Estimates
    • 2017-2021 American Community Survey 5-Year Estimates
    • 2016-2020 American Community Survey 5-Year Estimates
    • 2015-2019 American Community Survey 5-Year Estimates

    Variables / Data Columns

    • Rank by Non-Hispanic Black Population: This column displays the rank of cities in the Bethel Census Area, AK by their Non-Hispanic Black or African American population, using the most recent ACS data available.
    • cities: The cities for which the rank is shown in the previous column.
    • Non-Hispanic Black Population: The Non-Hispanic Black population of the cities is shown in this column.
    • % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic Black. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total Bethel Census Area Non-Hispanic Black Population: This tells us how much of the entire Bethel Census Area, AK Non-Hispanic Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  19. California City Boundaries and Identifiers

    • data.ca.gov
    • gis.data.ca.gov
    • +1more
    Updated Feb 26, 2025
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    California Department of Technology (2025). California City Boundaries and Identifiers [Dataset]. https://data.ca.gov/dataset/california-city-boundaries-and-identifiers
    Explore at:
    zip, kml, csv, gpkg, arcgis geoservices rest api, geojson, html, txt, gdb, xlsxAvailable download formats
    Dataset updated
    Feb 26, 2025
    Dataset authored and provided by
    California Department of Technologyhttp://cdt.ca.gov/
    Area covered
    California City
    Description

    WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of March 2025. The schema changed in February 2025 - please see below. We will post a roadmap of upcoming changes, but service URLs and schema are now stable. For deployment status of new services in February 2025, see https://gis.data.ca.gov/pages/city-and-county-boundary-data-status. Additional roadmap and status links at the bottom of this metadata.

    This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.

    Purpose

    City boundaries along with third party identifiers used to join in external data. Boundaries are from the California Department of Tax and Fee Administration (CDTFA). These boundaries are the best available statewide data source in that CDTFA receives changes in incorporation and boundary lines from the Board of Equalization, who receives them from local jurisdictions for tax purposes. Boundary accuracy is not guaranteed, and though CDTFA works to align boundaries based on historical records and local changes, errors will exist. If you require a legal assessment of boundary location, contact a licensed surveyor.

    This dataset joins in multiple attributes and identifiers from the US Census Bureau and Board on Geographic Names to facilitate adding additional third party data sources. In addition, we attach attributes of our own to ease and reduce common processing needs and questions. Finally, coastal buffers are separated into separate polygons, leaving the land-based portions of jurisdictions and coastal buffers in adjacent polygons. This feature layer is for public use.

    Related Layers

    This dataset is part of a grouping of many datasets:

    1. Cities: Only the city boundaries and attributes, without any unincorporated areas
    2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
    3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
    4. City and County Abbreviations
    5. Unincorporated Areas (Coming Soon)
    6. Census Designated Places
    7. Cartographic Coastline

    Working with Coastal Buffers
    The dataset you are currently viewing excludes the coastal buffers for cities and counties that have them in the source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except OFFSHORE and AREA_SQMI to get a version with the correct identifiers.

    Point of Contact

    California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

    Field and Abbreviation Definitions

    • CDTFA_CITY: CDTFA incorporated city name
    • CDTFA_COUNTY: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
    • CDTFA_COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system. The boundary data originate with CDTFA's teams managing tax rate information, so this field is preserved and flows into this dataset.
    • CENSUS_GEOID: numeric geographic identifiers from the US Census Bureau
    • CENSUS_PLACE_TYPE: City, County, or Town, stripped off the census name for identification purpose.
    • GNIS_PLACE_NAME: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
    • GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
    • CDT_CITY_ABBR: Abbreviations of incorporated area names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 4 characters. Not present in the county-specific layers.
    • CDT_COUNTY_ABBR: Abbreviations of county names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 3 characters.
    • CDT_NAME_SHORT: The name of the jurisdiction (city or county) with the word "City" or "County" stripped off the end. Some changes may come to how we process this value to make it more consistent.
    • AREA_SQMI: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
    • OFFSHORE: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
    • PRIMARY_DOMAIN: Currently empty/null for all records. Placeholder field for official URL of the city or county
    • CENSUS_POPULATION: Currently null for all records. In the future, it will include the most recent US Census population estimate for the jurisdiction.
    • GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to

  20. N

    cities in Southeast Fairbanks Census Area Ranked by Non-Hispanic Other Race...

    • neilsberg.com
    csv, json
    Updated Feb 11, 2025
    + more versions
    Share
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    Neilsberg Research (2025). cities in Southeast Fairbanks Census Area Ranked by Non-Hispanic Other Race Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/cities-in-southeast-fairbanks-census-area-ak-by-non-hispanic-other-race-population/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Southeast Fairbanks Census Area
    Variables measured
    Non-Hispanic Other Race Population, Non-Hispanic Other Race Population as Percent of Total Population of cities in Southeast Fairbanks Census Area, AK, Non-Hispanic Other Race Population as Percent of Total Non-Hispanic Other Race Population of Southeast Fairbanks Census Area, AK
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    This list ranks the 2 cities in the Southeast Fairbanks Census Area, AK by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

    • 2019-2023 American Community Survey 5-Year Estimates
    • 2018-2022 American Community Survey 5-Year Estimates
    • 2017-2021 American Community Survey 5-Year Estimates
    • 2016-2020 American Community Survey 5-Year Estimates
    • 2015-2019 American Community Survey 5-Year Estimates

    Variables / Data Columns

    • Rank by Non-Hispanic Other Race Population: This column displays the rank of cities in the Southeast Fairbanks Census Area, AK by their Non-Hispanic Some Other Race (SOR) population, using the most recent ACS data available.
    • cities: The cities for which the rank is shown in the previous column.
    • Non-Hispanic Other Race Population: The Non-Hispanic Other Race population of the cities is shown in this column.
    • % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total Southeast Fairbanks Census Area Non-Hispanic Other Race Population: This tells us how much of the entire Southeast Fairbanks Census Area, AK Non-Hispanic Other Race population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2016). Top 20 metropolitan areas in the United States in 2010, by land area [Dataset]. https://www.statista.com/statistics/431912/top-20-metropolitan-areas-in-the-united-states-by-land-area/
Organization logo

Top 20 metropolitan areas in the United States in 2010, by land area

Explore at:
Dataset updated
Feb 24, 2016
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2010
Area covered
United States
Description

This statistics shows a list of the top 20 largest-metropolitan areas in the United States in 2010, by land area. Riverside-San Bernardino-Ontario in California was ranked first enclosing an area of 70,612 square kilometers.

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