100+ datasets found
  1. Population density in California 1960-2018

    • statista.com
    Updated Apr 25, 2014
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    Statista (2014). Population density in California 1960-2018 [Dataset]. https://www.statista.com/statistics/304672/california-population-density/
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    Dataset updated
    Apr 25, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States, California
    Description

    This graph shows the population density in the federal state of California from 1960 to 2018. In 2018, the population density of California stood at 253.9 residents per square mile of land area.

  2. C

    California Urban Area Delineations

    • data.ca.gov
    Updated Dec 2, 2025
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    California Department of Finance (2025). California Urban Area Delineations [Dataset]. https://data.ca.gov/dataset/california-urban-area-delineations
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    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Dec 2, 2025
    Dataset provided by
    Calif. Dept. of Finance Demographic Research Unit
    Authors
    California Department of Finance
    Area covered
    California
    Description

    The Census Bureau released revised delineations for urban areas on December 29, 2022. The new criteria (contained in this Federal Register Notice) is based primarily on housing unit density measured at the census block level. The minimum qualifying threshold for inclusion as an urban area is an area that contains at least 2,000 housing units or has a population of at least 5,000 persons. It also eliminates the classification of areas as “urban clusters/urbanized areas”. This represents a change from 2010, where urban areas were defined as areas consisting of 50,000 people or more and urban clusters consisted of at least 2,500 people but less than 50,000 people with at least 1,500 people living outside of group quarters. Due to the new population thresholds for urban areas, 36 urban clusters in California are no longer considered urban areas, leaving California with 193 urban areas after the new criteria was implemented.

    The State of California experienced an increase of 1,885,884 in the total urban population, or 5.3%. However, the total urban area population as a percentage of the California total population went down from 95% to 94.2%. For more information about the mapped data, download the Excel spreadsheet here.

    Please note that some of the 2020 urban areas have different names or additional place names as a result of the inclusion of housing unit counts as secondary naming criteria.

    Please note there are four urban areas that cross state boundaries in Arizona and Nevada. For 2010, only the parts within California are displayed on the map; however, the population and housing estimates represent the entirety of the urban areas. For 2020, the population and housing unit estimates pertains to the areas within California only.

    Data for this web application was derived from the 2010 and 2020 Censuses (2010 and 2020 Census Blocks, 2020 Urban Areas, and Counties) and the 2016-2020 American Community Survey (2010 -Urban Areas) and can be found at data.census.gov.

    For more information about the urban area delineations, visit the Census Bureau's Urban and Rural webpage and FAQ.

    To view more data from the State of California Department of Finance, visit the Demographic Research Unit Data Hub.

  3. Resident population in California 1960-2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Resident population in California 1960-2023 [Dataset]. https://www.statista.com/statistics/206097/resident-population-in-california/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States, California
    Description

    In 2023, the resident population of California was ***** million. This is a slight decrease from the previous year, with ***** million people in 2022. This makes it the most populous state in the U.S. Californian demographics Along with an increase in population, California’s gross domestic product (GDP) has also been increasing, from *** trillion U.S. dollars in 2000 to **** trillion U.S. dollars in 2023. In the same time period, the per-capita personal income has almost doubled, from ****** U.S. dollars in 2000 to ****** U.S. dollars in 2022. In 2023, the majority of California’s resident population was Hispanic or Latino, although the number of white residents followed as a close second, with Asian residents making up the third-largest demographic in the state. The dark side of the Golden State While California is one of the most well-known states in the U.S., is home to Silicon Valley, and one of the states where personal income has been increasing over the past 20 years, not everyone in California is so lucky: In 2023, the poverty rate in California was about ** percent, and the state had the fifth-highest rate of homelessness in the country during that same year, with an estimated ** homeless people per 10,000 of the population.

  4. d

    MCNA - Population Points with T/D Standards

    • catalog.data.gov
    • healthdata.gov
    • +7more
    Updated Aug 23, 2025
    + more versions
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    California Department of Health Care Services (2025). MCNA - Population Points with T/D Standards [Dataset]. https://catalog.data.gov/dataset/mcna-population-points-with-t-d-standards-53349
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    Dataset updated
    Aug 23, 2025
    Dataset provided by
    California Department of Health Care Services
    Description

    Updated 10/6/2022: In the Time/Distance analysis process, points that were found to have been included initially, but with no significant or year-round population were removed. The layer of removed points is also available for viewing. MCNA - Removed Population PointsThe Network Adequacy Standards Representative Population Points feature layer contains 97,694 points spread across California that were created from USPS postal delivery route data and US Census data. Each population point also contains the variables for Time and Distance Standards for the County that the point is within. These standards differ by County due to the County "type" which is based on the population density of the county. There are 5 county categories within California: Rural (<50 people/sq mile), Small (51-200 people/sq mile), Medium (201-599 people/sq mile), and Dense (>600 people/sq mile). The Time and Distance data is divided out by Provider Type, Adult and Pediatric separately, so that the Time or Distance analysis can be performed with greater detail. HospitalsOB/GYN SpecialtyAdult Cardiology/Interventional CardiologyAdult DermatologyAdult EndocrinologyAdult ENT/OtolaryngologyAdult GastroenterologyAdult General SurgeryAdult HematologyAdult HIV/AIDS/Infectious DiseaseAdult Mental Health Outpatient ServicesAdult NephrologyAdult NeurologyAdult OncologyAdult OphthalmologyAdult Orthopedic SurgeryAdult PCPAdult Physical Medicine and RehabilitationAdult PsychiatryAdult PulmonologyPediatric Cardiology/Interventional CardiologyPediatric DermatologyPediatric EndocrinologyPediatric ENT/OtolaryngologyPediatric GastroenterologyPediatric General SurgeryPediatric HematologyPediatric HIV/AIDS/Infectious DiseasePediatric Mental Health Outpatient ServicesPediatric NephrologyPediatric NeurologyPediatric OncologyPediatric OphthalmologyPediatric Orthopedic SurgeryPediatric PCPPediatric Physical Medicine and RehabilitationPediatric PsychiatryPediatric Pulmonology

  5. d

    TIGER/Line Shapefile, 2019, state, California, Current Census Tract...

    • catalog.data.gov
    Updated Oct 12, 2021
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    (2021). TIGER/Line Shapefile, 2019, state, California, Current Census Tract State-based [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2019-state-california-current-census-tract-state-based
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    Dataset updated
    Oct 12, 2021
    Description

    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 2010 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.

  6. c

    California State Assembly Districts Map 2020

    • gis.data.ca.gov
    • data.ca.gov
    • +1more
    Updated Feb 9, 2023
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    California Department of Technology (2023). California State Assembly Districts Map 2020 [Dataset]. https://gis.data.ca.gov/datasets/1d4e5c18f82848afb7dbb2ce277f4c7d
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    Dataset updated
    Feb 9, 2023
    Dataset authored and provided by
    California Department of Technology
    Area covered
    Description

    Final approved map by the 2020 California Citizens Redistricting Commission for the California State Assembly; the authoritative and official delineations of the California State Assembly drawn during the 2020 redistricting cycle. The Citizens Redistricting Commission for the State of California has created statewide district maps for the State Assembly, State Senate, State Board of Equalization, and United States Congress in accordance, with the provisions of Article XXI of the California Constitution. The Commission has approved the final maps and certified them to the Secretary of State.Line drawing criteria included population equality as required by the U.S. Constitution, the Federal Voting Rights Act, geographic contiguity, geographic integrity, geographic compactness, and nesting. Geography was defined by U.S. Census Block geometry.80 Assembly districts have an ideal population of around 500,000 people each, and in consideration of population equality, the Commission chose to limit the population deviation range to as close to zero percent as practicable. With these districts, the Commission was able to respect many local communities of interest and group similar communities; however, it was more difficult to keep densely populated counties, cities, neighborhoods, and larger communities of interest whole due to the district size and correspondingly smaller number allowable in the population deviation percentage.

  7. California US Congressional Districts Map 2020

    • catalog.data.gov
    • data.ca.gov
    Updated Jul 24, 2025
    + more versions
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    California Citizens Redistricting Commission (2025). California US Congressional Districts Map 2020 [Dataset]. https://catalog.data.gov/dataset/california-us-congressional-districts-map-2020
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    California Citizens Redistricting Commission
    Area covered
    United States, California
    Description

    Final approved map by the 2020 California Citizens Redistricting Commission for California's United States Congressional Districts; the authoritative and official delineations of California's United States Congressional Districts drawn during the 2020 redistricting cycle. The Citizens Redistricting Commission for the State of California has created statewide district maps for the State Assembly, State Senate, State Board of Equalization, and United States Congress in accordance, with the provisions of Article XXI of the California Constitution. The Commission has approved the final maps and certified them to the Secretary of State.Line drawing criteria included population equality as required by the U.S. Constitution, the Federal Voting Rights Act, geographic contiguity, geographic integrity, geographic compactness, and nesting. Geography was defined by U.S. Census Block geometry.Each of the 52 Congressional districts apportioned to California have an ideal population of 760,066, and the Commission adhered to federal constitutional mandates by requiring a district population deviation of no more than +/- one person. These districts also posed some of the Commission’s biggest challenges, and, because of strict population equality requirements, resulted in many more splits of counties, cities, neighborhoods, and communities of interest compared to State Assembly or Senate plans.

  8. F

    Resident Population in California

    • fred.stlouisfed.org
    json
    Updated Dec 23, 2024
    + more versions
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    (2024). Resident Population in California [Dataset]. https://fred.stlouisfed.org/series/CAPOP
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    jsonAvailable download formats
    Dataset updated
    Dec 23, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    California
    Description

    Graph and download economic data for Resident Population in California (CAPOP) from 1900 to 2024 about residents, CA, population, and USA.

  9. CA Zip Code Boundaries

    • data.ca.gov
    • gis.data.ca.gov
    • +1more
    Updated Apr 16, 2025
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    California Department of Technology (2025). CA Zip Code Boundaries [Dataset]. https://data.ca.gov/dataset/ca-zip-code-boundaries
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    csv, arcgis geoservices rest api, geojson, gpkg, html, zip, txt, kml, gdb, xlsxAvailable download formats
    Dataset updated
    Apr 16, 2025
    Dataset authored and provided by
    California Department of Technologyhttp://cdt.ca.gov/
    Area covered
    California
    Description
    This feature service is derived from the Esri "United States Zip Code Boundaries" layer, queried to only CA data.


    Published by the California Department of Technology Geographic Information Services Team.
    The GIS Team can be reached at ODSdataservices@state.ca.gov.

    U.S. ZIP Code Boundaries represents five-digit ZIP Code areas used by the U.S. Postal Service to deliver mail more effectively. The first digit of a five-digit ZIP Code divides the United States into 10 large groups of states (or equivalent areas) numbered from 0 in the Northeast to 9 in the far West. Within these areas, each state is divided into an average of 10 smaller geographical areas, identified by the second and third digits. These digits, in conjunction with the first digit, represent a Sectional Center Facility (SCF) or a mail processing facility area. The fourth and fifth digits identify a post office, station, branch or local delivery area.

    As of the time this layer was published, in January 2025, Esri's boundaries are sourced from TomTom (June 2024) and the 2023 population estimates are from Esri Demographics. Esri updates its layer annually and those changes will immediately be reflected in this layer. Note that, because this layer passes through Esri's data, if you want to know the true date of the underlying data, click through to Esri's original source data and look at their metadata for more information on updates.

    Cautions about using Zip Code boundary data
    Zip code boundaries have three characteristics you should be aware of before using them:
    1. Zip code boundaries change, in ways small and large - these are not a stable analysis unit. Data you received keyed to zip codes may have used an earlier and very different boundary for your zip codes of interest.
    2. Historically, the United States Postal Service has not published zip code boundaries, and instead, boundary datasets are compiled by third party vendors from address data. That means that the boundary data are not authoritative, and any data you have keyed to zip codes may use a different, vendor-specific method for generating boundaries from the data here.
    3. Zip codes are designed to optimize mail delivery, not social, environmental, or demographic characteristics. Analysis using zip codes is subject to create issues with the Modifiable Areal Unit Problem that will bias any results because your units of analysis aren't designed for the data being studied.
    As of early 2025, USPS appears to be in the process of releasing boundaries, which will at least provide an authoritative source, but because of the other factors above, we do not recommend these boundaries for many use cases. If you are using these for anything other than mailing purposes, we recommend reconsideration. We provide the boundaries as a convenience, knowing people are looking for them, in order to ensure that up-to-date boundaries are available.
  10. California State Senate Districts Map 2020

    • catalog.data.gov
    • data.ca.gov
    • +1more
    Updated Jul 24, 2025
    + more versions
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    California Citizens Redistricting Commission (2025). California State Senate Districts Map 2020 [Dataset]. https://catalog.data.gov/dataset/california-state-senate-districts-map-2020
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    California Citizens Redistricting Commission
    Area covered
    California
    Description

    Final approved map by the 2020 California Citizens Redistricting Commission for the California State Senate; the authoritative and official delineations of the California State Senate drawn during the 2020 redistricting cycle. The Citizens Redistricting Commission for the State of California has created statewide district maps for the State Assembly, State Senate, State Board of Equalization, and United States Congress in accordance, with the provisions of Article XXI of the California Constitution. The Commission has approved the final maps and certified them to the Secretary of State.Line drawing criteria included population equality as required by the U.S. Constitution, the Federal Voting Rights Act, geographic contiguity, geographic integrity, geographic compactness, and nesting. Geography was defined by U.S. Census Block geometry.Each of the 40 Senate districts has an ideal population of nearly one million people and represents the largest state legislative districts in the nation. In consideration of population equality, the Commission chose to limit the population deviation as close to zero percent as practicable. Per the California Constitution, the Commission strived to nest two Assembly districts where practicable. However, higher ranking criteria made this difficult in practice. While the size of the Senate districts allowed the Commission to recognize broadly shared interests, these interests did not always overlap exactly with the interests of smaller communities recognized in the related Assembly districts. Based on the large number of people in each district, there were a variety of different interests that were balanced and included.

  11. Census of Population and Housing, 2000 [United States]: 1998 Dress...

    • icpsr.umich.edu
    ascii
    Updated Jan 12, 2006
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    United States. Bureau of the Census (2006). Census of Population and Housing, 2000 [United States]: 1998 Dress Rehearsal, P.L. 94-171 Redistricting Data, Geographic Files for 11 Counties in South Carolina, Sacramento, California, and Menominee County, Wisconsin [Dataset]. http://doi.org/10.3886/ICPSR02913.v1
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    asciiAvailable download formats
    Dataset updated
    Jan 12, 2006
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of the Census
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/2913/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/2913/terms

    Time period covered
    1998
    Area covered
    United States, South Carolina, Columbia, Wisconsin, Sacramento, South Carolina, California
    Description

    The 1998 Dress Rehearsal was conducted as a prelude to the United States Census of Population and Housing, 2000, in the following locations: (1) Columbia, South Carolina, and surrounding areas, including the town of Irmo and the counties of Chester, Chesterfield, Darlington, Fairfield, Kershaw, Lancaster, Lee, Marlboro, Newberry, Richland, and Union, (2) Sacramento, California, and (3) Menominee County, Wisconsin, including the Menominee American Indian Reservation. This collection contains map files showing various levels of geography (in the form of Census Tract Outline Maps, Voting District/State Legislative District Outline Maps, and County Block Maps), TIGER/Line digital files, and Corner Point files for the Census 2000 Dress Rehearsal sites. The Corner Point data files contain the bounding latitude and longitude coordinates for each individual map sheet of the 1998 Dress Rehearsal Public Law (P.L.) 94-171 map products. These files include a sheet identifier, minimum and maximum longitude, minimum and maximum latitude, and the map scale (integer value) for each map sheet. The latitude and longitude coordinates are in decimal degrees and expressed as integer values with six implied decimal places. There is a separate Corner Point File for each of the three map types: County Block Map, Census Tract Outline Map, and Voting District/State Legislative District Outline Map. Each of the three map file types is provided in two formats: Portable Document Format (PDF), for viewing, and Hewlett-Packard Graphics Language (HP-GL) format, for plotting. The County Block Maps show the greatest detail and the most complete set of geographic information of all the maps. These large-scale maps depict the smallest geographic entities for which the Census Bureau presents data -- the census blocks -- by displaying the features that delineate them and the numbers that identify them. These maps show the boundaries, names, and codes for American Indian/Alaska Native areas, county subdivisions, places, census tracts, and, for this series, the geographic entities that the states delineated in Phase 2, Voting District Project, of the Redistricting Data Program. The HP-GL version of the County Block Maps is broken down into index maps and map sheets. The map sheets cover a small area, and the index maps are composed of multiple map sheets, showing the entire area. The intent of the County Block Map series is to provide a map for each county on the smallest possible number of map sheets at the maximum practical scale, dependent on the area size of the county and the density of the block pattern. The latter affects the display of block numbers and feature identifiers. The Census Tract Outline Maps show the boundaries and numbers of census tracts, and name the features underlying the boundaries. These maps also show the boundaries and names of counties, county subdivisions, and places. They identify census tracts in relation to governmental unit boundaries. The mapping unit is the county. These large-format maps are produced to support the P.L. 94-171 program and all other 1998 Dress Rehearsal data tabulations. The Voting District/State Legislative District Outline Maps show the boundaries and codes for voting districts as delineated by the states in Phase 2, Voting District Project, of the Redistricting Data Program. The features underlying the voting district boundaries are shown, as well as the names of these features. Additionally, for states that submit the information, these maps show the boundaries and codes for state legislative districts and their underlying features. These maps also show the boundaries of and names of American Indian/Alaska Native areas, counties, county subdivisions, and places. The scale of the district maps is optimized to keep the number of map sheets for each area to a minimum, but the scale and number of map sheets will vary by the area size of the county and the voting districts and state legislative districts delineated by the states. The Census 2000 Dress Rehearsal TIGER/Line Files consist of line segments representing physical features and governmental and statistical boundaries. The files contain information distributed over a series of record types for the spatial objects of a county. These TIGER/Line Files are an extract of selected geographic and cartographic information from the Census TIGER (Topological

  12. Salmonid Population Monitoring Areas - California - CMP [ds3001]

    • data-cdfw.opendata.arcgis.com
    • data.ca.gov
    • +7more
    Updated May 15, 2025
    + more versions
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    California Department of Fish and Wildlife (2025). Salmonid Population Monitoring Areas - California - CMP [ds3001] [Dataset]. https://data-cdfw.opendata.arcgis.com/maps/f091d852919f49b3a6ca64f459222b73
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    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    California Department of Fish and Wildlifehttps://wildlife.ca.gov/
    License

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

    Area covered
    Description

    The California Monitoring Plan (CMP) salmonid monitoring areas and associated population data are part of an ongoing effort to summarize existing and past salmonid monitoring efforts in the areas identified by Adams et al. 2011. These data are compiled and maintained by the California Department of Fish and Wildlife with the cooperation of monitoring practitioners. Updates and associated outreach are intended to occur on an annual basis. Data were created from several sources and existing datasets: some monitoring areas were accurately depicted using the USGS National Hydrography Dataset (NHD), other monitoring areas were approximated using the monitoring point location and the USGS StreamStats tool to depict the watershed area above that point. The areas are intended to represent the approximate extent of sampling within sub-basins, watershed areas, or regions. For example, the spatial extent of monitoring using a fixed count station is approximated by accounting for all anadromous fish habitat upstream of the sampling location. Therefore, the area is approximated by entering the monitoring location coordinates into the StreamStats tool. The resulting shapefile is then examined to ensure the watershed area did not include habitat above dams or barriers to migration. Areas were clipped when needed. The data user should recognize that errors may have occurred during production of this dataset, changes may have occurred to the external sources used post transfer, and for other possible reasons. The population metrics summarized in the associated tabular data may be regarded as spatially limited, temporally limited, and not considered a complete estimate for the population being described. The data user is advised to refer to the annual reports cited in the Source field from the tabular data for additional details regarding monitoring within the area spatially depicted.Abbreviation Definitions: SGS = Spawning Ground Survey, RM = River Mile, RST = Rotary Screw Trap, RKM = River Kilometer, FCS = Fixed Count Station, STH = Steelhead, CC = Coastal Chinook, DS = Downstream

  13. K

    California 2020 Projected Urban Growth

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Oct 13, 2003
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    State of California (2003). California 2020 Projected Urban Growth [Dataset]. https://koordinates.com/layer/670-california-2020-projected-urban-growth/
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    geopackage / sqlite, mapinfo tab, kml, csv, mapinfo mif, geodatabase, dwg, pdf, shapefileAvailable download formats
    Dataset updated
    Oct 13, 2003
    Dataset authored and provided by
    State of California
    License

    https://koordinates.com/license/attribution-3-0/https://koordinates.com/license/attribution-3-0/

    Area covered
    Description

    20 year Projected Urban Growth scenarios. Base year is 2000. Projected year in this dataset is 2020.

    By 2020, most forecasters agree, California will be home to between 43 and 46 million residents-up from 35 million today. Beyond 2020 the size of California's population is less certain. Depending on the composition of the population, and future fertility and migration rates, California's 2050 population could be as little as 50 million or as much as 70 million. One hundred years from now, if present trends continue, California could conceivably have as many as 90 million residents.

    Where these future residents will live and work is unclear. For most of the 20th Century, two-thirds of Californians have lived south of the Tehachapi Mountains and west of the San Jacinto Mountains-in that part of the state commonly referred to as Southern California. Yet most of coastal Southern California is already highly urbanized, and there is relatively little vacant land available for new development. More recently, slow-growth policies in Northern California and declining developable land supplies in Southern California are squeezing ever more of the state's population growth into the San Joaquin Valley.

    How future Californians will occupy the landscape is also unclear. Over the last fifty years, the state's population has grown increasingly urban. Today, nearly 95 percent of Californians live in metropolitan areas, mostly at densities less than ten persons per acre. Recent growth patterns have strongly favored locations near freeways, most of which where built in the 1950s and 1960s. With few new freeways on the planning horizon, how will California's future growth organize itself in space? By national standards, California's large urban areas are already reasonably dense, and economic theory suggests that densities should increase further as California's urban regions continue to grow. In practice, densities have been rising in some urban counties, but falling in others.

    These are important issues as California plans its long-term future. Will California have enough land of the appropriate types and in the right locations to accommodate its projected population growth? Will future population growth consume ever-greater amounts of irreplaceable resource lands and habitat? Will jobs continue decentralizing, pushing out the boundaries of metropolitan areas? Will development densities be sufficient to support mass transit, or will future Californians be stuck in perpetual gridlock? Will urban and resort and recreational growth in the Sierra Nevada and Trinity Mountain regions lead to the over-fragmentation of precious natural habitat? How much water will be needed by California's future industries, farms, and residents, and where will that water be stored? Where should future highway, transit, and high-speed rail facilities and rights-of-way be located? Most of all, how much will all this growth cost, both economically, and in terms of changes in California's quality of life?

    Clearly, the more precise our current understanding of how and where California is likely to grow, the sooner and more inexpensively appropriate lands can be acquired for purposes of conservation, recreation, and future facility siting. Similarly, the more clearly future urbanization patterns can be anticipated, the greater our collective ability to undertake sound city, metropolitan, rural, and bioregional planning.

    Consider two scenarios for the year 2100. In the first, California's population would grow to 80 million persons and would occupy the landscape at an average density of eight persons per acre, the current statewide urban average. Under this scenario, and assuming that 10% percent of California's future population growth would occur through infill-that is, on existing urban land-California's expanding urban population would consume an additional 5.06 million acres of currently undeveloped land. As an alternative, assume the share of infill development were increased to 30%, and that new population were accommodated at a density of about 12 persons per acre-which is the current average density of the City of Los Angeles. Under this second scenario, California's urban population would consume an additional 2.6 million acres of currently undeveloped land. While both scenarios accommodate the same amount of population growth and generate large increments of additional urban development-indeed, some might say even the second scenario allows far too much growth and development-the second scenario is far kinder to California's unique natural landscape.

    This report presents the results of a series of baseline population and urban growth projections for California's 38 urban counties through the year 2100. Presented in map and table form, these projections are based on extrapolations of current population trends and recent urban development trends. The next section, titled Approach, outlines the methodology and data used to develop the various projections. The following section, Baseline Scenario, reviews the projections themselves. A final section, entitled Baseline Impacts, quantitatively assesses the impacts of the baseline projections on wetland, hillside, farmland and habitat loss.

  14. 2020 Cartographic Boundary File (KML), Current Census Tract for California,...

    • 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), Current Census Tract for California, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2020-cartographic-boundary-file-kml-current-census-tract-for-california-1-500000
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    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    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. 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 and beyond, 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.

  15. s

    Population Density Per Acre: San Francisco Bay Area, California, 2000

    • searchworks.stanford.edu
    zip
    Updated May 4, 2021
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    (2021). Population Density Per Acre: San Francisco Bay Area, California, 2000 [Dataset]. https://searchworks.stanford.edu/view/bf412pw9968
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    zipAvailable download formats
    Dataset updated
    May 4, 2021
    Area covered
    San Francisco Bay Area, California
    Description

    This raster dataset depicts the population denisty of the nine county San Francisco Bay Area Region, California produced with a Dasymetric Mapping Technique, which is used to depict quantitative areal data using boundaries that divide an area into zones of relative homogeneity with the purpose of better portraying the population distribution. The source data was then adjusted in order to get convert the units to persons per acre. This dataset is an accurate representation of population distribution within census boundaries and can be used in a number of ways, including as the Conservation Suitability layer for the Marxan inputs and the watershed integrity analysis.

  16. Medical Service Study Areas

    • healthdata.gov
    • data.ca.gov
    • +5more
    csv, xlsx, xml
    Updated Apr 8, 2025
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    chhs.data.ca.gov (2025). Medical Service Study Areas [Dataset]. https://healthdata.gov/State/Medical-Service-Study-Areas/nvx2-hzzm
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    chhs.data.ca.gov
    Description
    This is the current Medical Service Study Area. California Medical Service Study Areas are created by the California Department of Health Care Access and Information (HCAI).

    Check the Data Dictionary for field descriptions.


    Checkout the California Healthcare Atlas for more Medical Service Study Area information.

    This is an update to the MSSA geometries and demographics to reflect the new 2020 Census tract data. The Medical Service Study Area (MSSA) polygon layer represents the best fit mapping of all new 2020 California census tract boundaries to the original 2010 census tract boundaries used in the construction of the original 2010 MSSA file. Each of the state's new 9,129 census tracts was assigned to one of the previously established medical service study areas (excluding tracts with no land area), as identified in this data layer. The MSSA Census tract data is aggregated by HCAI, to create this MSSA data layer. This represents the final re-mapping of 2020 Census tracts to the original 2010 MSSA geometries. The 2010 MSSA were based on U.S. Census 2010 data and public meetings held throughout California.


    <a href="https://hcai.ca.gov/">https://hcai.ca.gov/</a>

    Source of update: American Community Survey 5-year 2006-2010 data for poverty. For source tables refer to InfoUSA update procedural documentation. The 2010 MSSA Detail layer was developed to update fields affected by population change. The American Community Survey 5-year 2006-2010 population data pertaining to total, in households, race, ethnicity, age, and poverty was used in the update. The 2010 MSSA Census Tract Detail map layer was developed to support geographic information systems (GIS) applications, representing 2010 census tract geography that is the foundation of 2010 medical service study area (MSSA) boundaries. ***This version is the finalized MSSA reconfiguration boundaries based on the US Census Bureau 2010 Census. In 1976 Garamendi Rural Health Services Act, required the development of a geographic framework for determining which parts of the state were rural and which were urban, and for determining which parts of counties and cities had adequate health care resources and which were "medically underserved". Thus, sub-city and sub-county geographic units called "medical service study areas [MSSAs]" were developed, using combinations of census-defined geographic units, established following General Rules promulgated by a statutory commission. After each subsequent census the MSSAs were revised. In the scheduled revisions that followed the 1990 census, community meetings of stakeholders (including county officials, and representatives of hospitals and community health centers) were held in larger metropolitan areas. The meetings were designed to develop consensus as how to draw the sub-city units so as to best display health care disparities. The importance of involving stakeholders was heightened in 1992 when the United States Department of Health and Human Services' Health and Resources Administration entered a formal agreement to recognize the state-determined MSSAs as "rational service areas" for federal recognition of "health professional shortage areas" and "medically underserved areas". After the 2000 census, two innovations transformed the process, and set the stage for GIS to emerge as a major factor in health care resource planning in California. First, the Office of Statewide Health Planning and Development [OSHPD], which organizes the community stakeholder meetings and provides the staff to administer the MSSAs, entered into an Enterprise GIS contract. Second, OSHPD authorized at least one community meeting to be held in each of the 58 counties, a significant number of which were wholly rural or frontier counties. For populous Los Angeles County, 11 community meetings were held. As a result, health resource data in California are collected and organized by 541 geographic units. The boundaries of these units were established by community healthcare experts, with the objective of maximizing their usefulness for needs assessment purposes. The most dramatic consequence was introducing a data simultaneously displayed in a GIS format. A two-person team, incorporating healthcare policy and GIS expertise, conducted the series of meetings, and supervised the development of the 2000-census configuration of the MSSAs.

    MSSA Configuration Guidelines (General Rules):- Each MSSA is composed of one or more complete census tracts.- As a general rule, MSSAs are deemed to be "rational service areas [RSAs]" for purposes of designating health professional shortage areas [HPSAs], medically underserved areas [MUAs] or medically underserved populations [MUPs].- MSSAs will not cross county lines.- To the extent practicable, all census-defined places within the MSSA are within 30 minutes travel time to the largest population center within the MSSA, except in those circumstances where meeting this criterion would require splitting a census tract.- To the extent practicable, areas that, standing alone, would meet both the definition of an MSSA and a Rural MSSA, should not be a part of an Urban MSSA.- Any Urban MSSA whose population exceeds 200,000 shall be divided into two or more Urban MSSA Subdivisions.- Urban MSSA Subdivisions should be within a population range of 75,000 to 125,000, but may not be smaller than five square miles in area. If removing any census tract on the perimeter of the Urban MSSA Subdivision would cause the area to fall below five square miles in area, then the population of the Urban MSSA may exceed 125,000. - To the extent practicable, Urban MSSA Subdivisions should reflect recognized community and neighborhood boundaries and take into account such demographic information as income level and ethnicity. Rural Definitions: A rural MSSA is an MSSA adopted by the Commission, which has a population density of less than 250 persons per square mile, and which has no census defined place within the area with a population in excess of 50,000. Only the population that is located within the MSSA is counted in determining the population of the census defined place. A frontier MSSA is a rural MSSA adopted by the Commission which has a population density of less than 11 persons per square mile. Any MSSA which is not a rural or frontier MSSA is an urban MSSA. Last updated December 6th 2024.
  17. F

    Resident Population in Los Angeles County, CA

    • fred.stlouisfed.org
    json
    Updated Mar 14, 2025
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    (2025). Resident Population in Los Angeles County, CA [Dataset]. https://fred.stlouisfed.org/series/CALOSA7POP
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    jsonAvailable download formats
    Dataset updated
    Mar 14, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    California, Los Angeles County
    Description

    Graph and download economic data for Resident Population in Los Angeles County, CA (CALOSA7POP) from 1970 to 2024 about Los Angeles County, CA; Los Angeles; residents; CA; population; and USA.

  18. T

    Resident Population in California

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Nov 27, 2017
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    TRADING ECONOMICS (2017). Resident Population in California [Dataset]. https://tradingeconomics.com/united-states/resident-population-in-california-thous-of-persons-a-na-fed-data.html
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Nov 27, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    California
    Description

    Resident Population in California was 39431.26300 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, Resident Population in California reached a record high of 39521.95800 in January of 2020 and a record low of 1490.00000 in January of 1900. Trading Economics provides the current actual value, an historical data chart and related indicators for Resident Population in California - last updated from the United States Federal Reserve on December of 2025.

  19. G

    Distribution of Population 1851-1941

    • open.canada.ca
    • datasets.ai
    • +1more
    jpg, pdf
    Updated Mar 14, 2022
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    Natural Resources Canada (2022). Distribution of Population 1851-1941 [Dataset]. https://open.canada.ca/data/en/dataset/48a638ed-1850-55b9-9b2b-348d7ee1e5df
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    pdf, jpgAvailable download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Natural Resources Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows the distribution of population in what is now Canada circa 1851, 1871, 1901, 1921 and 1941. The five maps display the boundaries of the various colonies, provinces and territories for each date. Also shown on these five maps are the locations of principal cities and settlements. These places are shown on all of the maps for reference purposes even though they may not have been in existence in the earlier years. Each map is accompanied by a pie chart providing the percentage distribution of Canadian population by province and territory corresponding to the date the map is based on. It should be noted that the pie chart entitled Percentage Distribution of Total Population, 1851, refers to the whole of what was then British North America. The name Canada in this chart refers to the province of Canada which entered confederation in 1867 as Ontario and Quebec. The other pie charts, however, show only percentage distribution of population in what was Canada at the date indicated. Three additional graphs are included on this plate and show changes in the distribution of the population of Canada from 1867 to 1951, changes in the percentage distribution of the population of Canada by provinces and territories from 1867 to 1951 and elements in the growth of the population of Canada for each ten-year period from 1891 to 1951.

  20. g

    California State Assembly Districts Map 2020 | gimi9.com

    • gimi9.com
    Updated Mar 6, 2023
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    (2023). California State Assembly Districts Map 2020 | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_california-state-assembly-districts-map-2020/
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    Dataset updated
    Mar 6, 2023
    Area covered
    California
    Description

    80 Assembly districts have an ideal population of around 500,000 people each, and in consideration of population equality, the Commission chose to limit the population deviation range to as close to zero percent as practicable. With these districts, the Commission was able to respect many local communities of interest and group similar communities; however, it was more difficult to keep densely populated counties, cities, neighborhoods, and larger communities of interest whole due to the district size and correspondingly smaller number allowable in the population deviation percentage.

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Statista (2014). Population density in California 1960-2018 [Dataset]. https://www.statista.com/statistics/304672/california-population-density/
Organization logo

Population density in California 1960-2018

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Dataset updated
Apr 25, 2014
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States, California
Description

This graph shows the population density in the federal state of California from 1960 to 2018. In 2018, the population density of California stood at 253.9 residents per square mile of land area.

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