32 datasets found
  1. San Francisco Bay Region Counties (clipped)

    • opendata-mtc.opendata.arcgis.com
    • opendata.mtc.ca.gov
    • +1more
    Updated Nov 3, 2021
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    MTC/ABAG (2021). San Francisco Bay Region Counties (clipped) [Dataset]. https://opendata-mtc.opendata.arcgis.com/datasets/15e88533ab3c488a853ed32a438ad4c4
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    Dataset updated
    Nov 3, 2021
    Dataset provided by
    Association of Bay Area Governmentshttps://abag.ca.gov/
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    County boundaries for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from, and clipped using, California 2020 TIGER/Line shapefiles by the Metropolitan Transportation Commission. The 2020 TIGER/Line Shapefiles reflect available governmental unit boundaries of the counties and equivalent entities as of May 28, 2021.Counties and equivalent entities are primary legal divisions of states. In most states, these entities are termed “counties.” Each county or statistically equivalent entity is assigned a 3-character FIPS code that is unique within a state.

  2. T

    Vital Signs: Commute Time (by Place of Residence) – by county (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 4, 2023
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    (2023). Vital Signs: Commute Time (by Place of Residence) – by county (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Commute-Time-by-Place-of-Residence-by-/5bqp-dsj6
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    application/rssxml, csv, json, xml, application/rdfxml, tsvAvailable download formats
    Dataset updated
    Jan 4, 2023
    Description

    VITAL SIGNS INDICATOR
    Commute Time (T3)

    FULL MEASURE NAME
    Commute time by residential location

    LAST UPDATED
    January 2023

    DESCRIPTION
    Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.

    DATA SOURCE
    U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation.htm

    U.S. Census Bureau: American Community Survey - https://data.census.gov/
    2006-2021
    Form C08136
    Form C08536
    Form B08301
    Form B08301
    Form B08301

    CONTACT INFORMATION
    vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.

    For the American Community Survey (ACS) datasets, 1-year rolling average data was used for all metros, region and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.

    Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute times were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography.

    Census tract data is not available for tracts with insufficient numbers of residents. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary metropolitan statistical areas (MSAs) for the nine other major metropolitan areas.

  3. T

    Vital Signs: Population – by county

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Oct 31, 2019
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    California Department of Finance (2019). Vital Signs: Population – by county [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Population-by-county/53v3-ss53
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    application/rssxml, csv, xml, json, tsv, application/rdfxmlAvailable download formats
    Dataset updated
    Oct 31, 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

  4. a

    San Francisco Bay Region 2020 Census Block Groups (clipped)

    • hub.arcgis.com
    • opendata.mtc.ca.gov
    • +1more
    Updated Dec 3, 2021
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    MTC/ABAG (2021). San Francisco Bay Region 2020 Census Block Groups (clipped) [Dataset]. https://hub.arcgis.com/datasets/31782b7e205f41fe8835ec52eec84fe4
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    Dataset updated
    Dec 3, 2021
    Dataset authored and provided by
    MTC/ABAG
    Area covered
    Description

    2020 Census block groups for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from California 2021 TIGER/Line shapefile by the Metropolitan Transportation Commission.Block groups are clusters of blocks within the same census tract. Each census tract contains at least one block group, and block groups are uniquely numbered within census tracts. Block groups have a valid code range of 0 through 9. Block groups have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within Block Group 3 within that census tract. Block groups coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas.Block groups generally contain between 600 and 3,000 people. A block group usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian/Alaska Native/Native Hawaiian areas. The block group boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

  5. San Francisco Bay Region Incorporated Cities and Towns (clipped)

    • opendata-mtc.opendata.arcgis.com
    • opendata.mtc.ca.gov
    • +1more
    Updated Nov 3, 2021
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    MTC/ABAG (2021). San Francisco Bay Region Incorporated Cities and Towns (clipped) [Dataset]. https://opendata-mtc.opendata.arcgis.com/datasets/san-francisco-bay-region-incorporated-cities-and-towns-clipped-1
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    Dataset updated
    Nov 3, 2021
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Incorporated Places (cities and towns) are those reported to the Census Bureau as legally in existence as of May 28, 2021, under the laws of their respective states. Features were extracted from, and clipped using, California 2020 TIGER/Line shapefiles by the Metropolitan Transportation Commission. An incorporated place provides governmental functions for a concentration of people, as opposed to a minor civil division, which generally provides services or administers an area without regard, necessarily, to population. Places may extend across county and county subdivision boundaries, but never across state boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions.

  6. T

    Vital Signs: Commute Mode Choice (by Place of Residence) – Bay Area (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Nov 29, 2023
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    (2023). Vital Signs: Commute Mode Choice (by Place of Residence) – Bay Area (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Commute-Mode-Choice-by-Place-of-Reside/nmtw-k5b6
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    xml, application/rssxml, application/rdfxml, csv, json, tsvAvailable download formats
    Dataset updated
    Nov 29, 2023
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR
    Commute Mode Choice (T1)

    FULL MEASURE NAME
    Commute mode share by residential location

    LAST UPDATED
    January 2023

    DESCRIPTION
    Commute mode choice, also known as commute mode share, refers to the mode of transportation that a commuter usually uses to travel to work, such as driving alone, biking, carpooling or taking transit. The dataset includes metropolitan area, regional, county, city and census tract tables by place of residence.

    DATA SOURCE
    U.S. Census Bureau: Decennial Census (1960, 1970) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation/Means19602000.htm

    U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation/Means19802000.htm

    U.S. Census Bureau: American Community Survey - https://data.census.gov/
    2006-2021
    Form B08301 (1-year and 5-year)

    CONTACT INFORMATION
    vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    Commute mode choice, also known as commute mode share, refers to the mode of transportation that a commuter usually uses to travel to work, such as driving alone, biking, carpooling or taking transit. For the decennial Census datasets, the breakdown of auto commuters between drive alone and carpool is not available before 1980. American Community Survey 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. This will result in discrepancies in cases like San Francisco where it is both a city and a county. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020. Additionally, for the County by place of residence breakdown, Napa was missing ACS 1-Year commute mode choice data for all modes for 2007, 2008, 2011 and 2021. 5-Year estimates were used to fill the missing data for 2011 and 2021, but not 2007 or 2008 since the 5-Year estimates start in 2009.

    Regional mode shares are population-weighted averages of the nine counties' modal shares. "Auto" includes drive alone and carpool for the simple data tables and is broken out in the detailed data tables accordingly, as it was not available before 1980. "Transit" includes public operators (Muni, BART, etc.) and employer-provided shuttles (e.g., Google shuttle buses). "Other" includes motorcycle, taxi, and other modes of transportation; bicycle mode share was broken out separately for the first time in the 2006 data and is shown in the detailed data tables. Census tract data is not available for tracts with insufficient numbers of residents or workers.

    The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary metropolitan statistical areas (MSAs) for other major metropolitan areas.

  7. San Francisco Bay Region 2020 Census Block Groups

    • opendata.mtc.ca.gov
    • hub.arcgis.com
    Updated Dec 2, 2021
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    MTC/ABAG (2021). San Francisco Bay Region 2020 Census Block Groups [Dataset]. https://opendata.mtc.ca.gov/items/d5f1d92f903c48d0b59f05d83f6089f9
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    Dataset updated
    Dec 2, 2021
    Dataset provided by
    Metropolitan Transportation Commission
    Association of Bay Area Governmentshttps://abag.ca.gov/
    Authors
    MTC/ABAG
    Area covered
    Description

    2020 Census block groups for the San Francisco Bay Region. Features were extracted from California 2021 TIGER/Line shapefile by the Metropolitan Transportation Commission.Block groups are clusters of blocks within the same census tract. Each census tract contains at least one block group, and block groups are uniquely numbered within census tracts. Block groups have a valid code range of 0 through 9. Block groups have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within Block Group 3 within that census tract. Block groups coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas.Block groups generally contain between 600 and 3,000 people. A block group usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian/Alaska Native/Native Hawaiian areas. The block group boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

  8. a

    San Francisco Bay Region 2010 Census Tracts (clipped)

    • hub.arcgis.com
    • opendata.mtc.ca.gov
    Updated Jun 20, 2019
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    ABAG/MTC (2019). San Francisco Bay Region 2010 Census Tracts (clipped) [Dataset]. https://hub.arcgis.com/datasets/795ff16162684d08827e8ad89b76abb4_5
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    Dataset updated
    Jun 20, 2019
    Dataset authored and provided by
    ABAG/MTC
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    2010 Census tracts for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from, and clipped using, California 2018 TIGER/Line shapefiles by the Metropolitan Transportation Commission.Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and are reviewed and updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP). The Census Bureau updates census tracts in situations where no local participant existed or where local or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data.Census tracts generally have a population size between 1,200 and 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts.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 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.Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix; for example, 1457.02. The census tract numbers (used as names) eliminate any leading zeroes and append a suffix only if required. The 6-character numeric census tract codes, however, include leading zeroes and have an implied decimal point for the suffix. Census tract codes range from 000100 to 998999 and are unique within a county or equivalent area. The Census Bureau assigned a census tract code of 9900 to represent census tracts delineated to cover large bodies of water. In addition, census tract codes in the 9400s represent American Indian Areas and codes in the 9800s represent special land use areas.The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes.Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

  9. T

    Vital Signs: Commute Time (by Place of Residence) – Bay Area (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 4, 2023
    + more versions
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    (2023). Vital Signs: Commute Time (by Place of Residence) – Bay Area (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Commute-Time-by-Place-of-Residence-Bay/jgx3-k2u8
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    csv, application/rssxml, xml, application/rdfxml, tsv, jsonAvailable download formats
    Dataset updated
    Jan 4, 2023
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR
    Commute Time (T3)

    FULL MEASURE NAME
    Commute time by residential location

    LAST UPDATED
    January 2023

    DESCRIPTION
    Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.

    DATA SOURCE
    U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation.htm

    U.S. Census Bureau: American Community Survey - https://data.census.gov/
    2006-2021
    Form C08136
    Form C08536
    Form B08301
    Form B08301
    Form B08301

    CONTACT INFORMATION
    vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.

    For the American Community Survey (ACS) datasets, 1-year rolling average data was used for all metros, region and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.

    Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute times were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography.

    Census tract data is not available for tracts with insufficient numbers of residents. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary metropolitan statistical areas (MSAs) for the nine other major metropolitan areas.

  10. Vital Signs: Commute Mode Choice (by Place of Employment) – by county

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Apr 16, 2020
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    U.S. Census Bureau (2020). Vital Signs: Commute Mode Choice (by Place of Employment) – by county [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Commute-Mode-Choice-by-Place-of-Employ/h527-iddw
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    xml, tsv, csv, application/rdfxml, application/rssxml, jsonAvailable download formats
    Dataset updated
    Apr 16, 2020
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau
    Description

    VITAL SIGNS INDICATOR Commute Mode Choice (T2)

    FULL MEASURE NAME Commute mode share by employment location

    LAST UPDATED April 2020

    DESCRIPTION Commute mode choice, also known as commute mode share, refers to the mode of transportation that a commuter uses to travel to work, such as driving alone, biking, carpooling or taking transit. The dataset includes metropolitan area, regional, county, city and census tract tables by place of work.

    DATA SOURCE U.S. Census Bureau: Decennial Census (1960-2000) - via MTC/ABAG Bay Area Census http://www.bayareacensus.ca.gov/transportation/Means19802000.htm

    U.S. Census Bureau: American Community Survey Form B08601 (2018 only; place of employment) www.api.census.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) For the decennial Census datasets, the breakdown of auto commuters between drive alone and carpool is not available before 1980. "Other" includes bicycle, motorcycle, taxi, and other modes of transportation.

    For the American Community Survey datasets, 1-year rolling average data was used for metros, region, and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Regional mode share was calculated using county modal data and calculating the weighted average based on county populations. "Auto" includes drive alone and carpool for the simple data tables and is broken out in the detailed data tables accordingly, as it was not available before 1980. "Other" includes motorcycle, taxi, and other modes of transportation; bicycle mode share is broken out separately for the first time in the 2006 data and is shown in the detailed data tables. Census tract data is not available for tracts with insufficient numbers of residents. Data for Napa County were not available due to small sample size.

    The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary MSAs for the nine other major metropolitan areas.

  11. San Francisco Bay Region Jurisdictions (Incorporated Places and...

    • opendata-mtc.opendata.arcgis.com
    • opendata.mtc.ca.gov
    • +2more
    Updated Nov 3, 2021
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    MTC/ABAG (2021). San Francisco Bay Region Jurisdictions (Incorporated Places and Unincorporated County Lands) [Dataset]. https://opendata-mtc.opendata.arcgis.com/datasets/san-francisco-bay-region-jurisdictions-incorporated-places-and-unincorporated-county-lands
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    Dataset updated
    Nov 3, 2021
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    The San Francisco Bay Region Jurisdictions feature set was developed by the Metropolitan Transportation Commission so tables containing values for both incorporated and unincorporated areas could be joined to a spatial feature set for mapping and analysis. County-level, 2020 TIGER/Line shapefiles were used to develop this feature set.Incorporated places (cities and towns) were erased from the county features for the region. The remaining county areas (unincorporated lands) were then added to the incorporated places to produce a full, incorporated-unincorporated feature set for the region.

  12. a

    San Francisco Bay Region 2010 Census Tracts (clipped)

    • hub.arcgis.com
    Updated Nov 23, 2022
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    MTC/ABAG (2022). San Francisco Bay Region 2010 Census Tracts (clipped) [Dataset]. https://hub.arcgis.com/maps/MTC::san-francisco-bay-region-2010-census-tracts-clipped
    Explore at:
    Dataset updated
    Nov 23, 2022
    Dataset authored and provided by
    MTC/ABAG
    Area covered
    Description

    This feature layer contains census tracts for the San Francisco Bay Region for Census 2010. The features were extracted from a statewide data set downloaded from the United States Census Bureau by Metropolitan Transportation Commission staff.The purpose of this feature layer is for the production of feature sets for public access and download to avoid licensing issues related to the agency's base data.Source data downloaded from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html_The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the United States 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 File 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 Census 2010 Participant Statistical Areas Program (PSAP). 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 1,500 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, etc. may require boundary revisions before a census. 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 are always 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.

  13. San Francisco Bay Region 2020 Census Tracts

    • opendata-mtc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Dec 2, 2021
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    MTC/ABAG (2021). San Francisco Bay Region 2020 Census Tracts [Dataset]. https://opendata-mtc.opendata.arcgis.com/datasets/san-francisco-bay-region-2020-census-tracts/about
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    Dataset updated
    Dec 2, 2021
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    Area covered
    Description

    2020 Census tracts for the San Francisco Bay Region. Features were extracted from California 2021 TIGER/Line shapefile by the Metropolitan Transportation Commission.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.The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes.Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

  14. San Francisco Bay Region Roadways

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • opendata.mtc.ca.gov
    • +2more
    Updated Dec 3, 2021
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    MTC/ABAG (2021). San Francisco Bay Region Roadways [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/cc308da7798a4b03926e22c1f815d553
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    Dataset updated
    Dec 3, 2021
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    Area covered
    Description

    Roadways (streets and highways) for the San Francisco Bay Region. Feature set was assembled using all roads county-based 2021 TIGER/Line shapefiles by the Metropolitan Transportation Commission.The All Roads shapefiles includes all features within the Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB) Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, stairways, and winter trails.The feature set contains multiple overlapping road segments where a segment is associated with more than one road feature. For example, if a road segment is associated with US Route 36 and State Highway 7 and 28th Street, the route will contain three spatially coincident segments, each with a different name. The roadway feature set contains the set of unique road segments for each county, along with other linear features.Primary roads are generally divided limited-access highways within the Federal interstate highway system or under state management. Interchanges and ramps distinguish these roads, and some are toll highways.Secondary roads are main arteries, usually in the U.S. highway, state highway, or county highway system. These roads have one or more lanes of traffic in each direction, may or may not be divided, and usually have at-grade intersections with many other roads and driveways. They often have both a local name and a route number.

  15. Projections 2040 by County: Jobs and Employment

    • opendata.mtc.ca.gov
    • hub.arcgis.com
    Updated Jul 17, 2019
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    MTC/ABAG (2019). Projections 2040 by County: Jobs and Employment [Dataset]. https://opendata.mtc.ca.gov/datasets/20b33a1efd5e4e88b60e5f306c597046
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    Dataset updated
    Jul 17, 2019
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This feature set contains jobs and employment projections from Projections 2040 for the San Francisco Bay Region. This forecast represents job and employment projections resulting from Plan Bay Area 2040. Numbers are provided by county. Jobs and employment numbers are included for 2010 (two versions), 2015, 2020, 2025, 2030, 2035, and 2040. For 2010, two data points are provided:A tabulation (base year A) from the 2010 model simulation (base year A); and(Preferred) A tabulation (base year B) from the 2010 pre-run microdata, designed to approximate (but may still differ from) Census 2010 counts.Projection data is included for:Agriculture and natural resources jobsFinancial and professional service jobsHealth, educational, and recreational service jobsManufacturing, wholesale, and transportation jobsInformation, government, and construction jobsRetail jobsTotal jobsEmployed residentsThis feature set was assembled using unclipped county features. For those who prefer Projections 2040 data using county features with ocean and bay waters clipped out, the data in this feature service can be joined to San Francisco Bay Region Counties (clipped).Other Projections 2040 feature sets:Households and population per countyHouseholds and population per jurisdiction (incorporated place and unincorporated county)Households and population per Census TractJobs and employment per jurisdiction (incorporated place and unincorporated county)Jobs per Census TractFemale population, by age range, per countyFemale population, by age range, per jurisdiction (incorporated place and unincorporated county)Male population, by age range, per countyMale population, by age range, per jurisdiction (incorporated place and unincorporated county)Total population, by age range, per countyTotal population, by age range, per jurisdiction (incorporated place and unincorporated county)

  16. M

    Vital Signs: Poverty - Bay Area

    • open-data-demo.mtc.ca.gov
    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 8, 2019
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    U.S. Census Bureau (2019). Vital Signs: Poverty - Bay Area [Dataset]. https://open-data-demo.mtc.ca.gov/widgets/38fe-vd33
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    xml, application/rssxml, csv, tsv, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Jan 8, 2019
    Dataset authored and provided by
    U.S. Census Bureau
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR Poverty (EQ5)

    FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

    LAST UPDATED December 2018

    DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

    DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

    U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

    METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

    For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

    For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

    To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

  17. Plan Bay Area 2040 Forecast - Population and Demographics

    • opendata.mtc.ca.gov
    • opendata-mtc.opendata.arcgis.com
    • +1more
    Updated Jul 2, 2018
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    MTC/ABAG (2018). Plan Bay Area 2040 Forecast - Population and Demographics [Dataset]. https://opendata.mtc.ca.gov/datasets/plan-bay-area-2040-forecast-population-and-demographics
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    Dataset updated
    Jul 2, 2018
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    San Francisco Bay Area
    Description

    Table of population and demographic forecast numbers from Plan Bay Area 2040 for the San Francisco Bay Region. Population and demographic numbers are included for 2005, 2010, 2015, 2020, 2030, 2035, and 2040. There are no forecast numbers for 2025.The Plan Bay Area forecast numbers were generated by Transportation Analysis Zone (TAZ). The Population and Demographics forecast table will need to be joined to TAZ features in order to spatially visualize the data. The TAZ features are available for download here.2005-2040 data in this table:Total PopulationHousehold PopulationGroup Quarters Population0 - 4 Age Group5 - 19 Age Group20 - 44 Age Group44 - 64 Age Group65+ Age GroupShare of Total Population that is 62 and OverHigh School EnrollmentCollege Enrollment (full-time)College Enrollment (part-time)Other Plan Bay Area 2040 forecast tables:Employment (total employment, TAZ resident employment, retail employment, financial and professional services employment, health, educational, and recreational employment, manufacturing, wholesale, and transportation employment, agricultural and natural resources employment, and other employment)Households (number of households and household income quartile)Land Use and Transportation (area type, commercial or industrial acres, residential acres, number of single-family and multi-family dwelling units, time to get from automobile storage location to origin/destination, and hourly parking rates)

  18. d

    Pedestrian Volume Model Data (2011 Study).

    • datadiscoverystudio.org
    • data.wu.ac.at
    csv, json
    Updated Mar 28, 2018
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    (2018). Pedestrian Volume Model Data (2011 Study). [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/b0ee66b6709c4ea184e10ef4fffc1b5f/html
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    json, csvAvailable download formats
    Dataset updated
    Mar 28, 2018
    Description

    description: | A. PURPOSE | This dataset is created to show the estimated yearly pedestrian volume at each intersection. | B. METHODOLOGY | http://archives.sfmta.com/cms/rpedmast/documents/FinalPedestrianCountReport6_17_11.pdf | C. UPDATE FREQUENCY | Not updated | D. OTHER CRITICAL INFO | Volume estimates made with 2011 transportation data and 2000 US Census data | E. ATTRIBUTES | CNN: San Francisco's street centerline network unique ID; ST_NAME1: Name of cross street;ST_TYPE1: Type of street;ST_NAME2: Name of cross street;ST_TYPE2: Type of street;ST_NAME3: Name of cross street;ST_TYPE3: Type of street;ST_NAME4: Name of cross street;ST_TYPE4: Type of street;TOTEMP2: Total number of jobs within 0.25 miles of the intersection in 2010. Data calculated by SFCTA from SFCTA traffic analysis zones. These data are produced by the SF Planning Department by allocating ABAG countylevel land use figures to the SFCTA's 981 transportation analysis zones within San Francisco;UNIVPROX: Intersection is located within 0.25 miles of one the five major university campuses in the city: USF Lone Mountain, UCSF Parnassus, UCSF Mission Bay, City College Ingleside, SFSU Park Merced. Other schools are not included, since they are either smaller, more spread out, or different in character (e.g., serve adult/commuter students at night). (1 = yes, 0 = no);Signalized: Intersection is controlled by a traffic signal. (1 = yes, 0 = no); PkgMeters: Intersection is in a zone with parking meters (e.g., parking meters are present on at least one approach to the intersection). (1 = yes, 0 =no); MaxPctSlpe: Maximum slope of any approach to the intersection. (Percent slope); Model6_Vol: Annual pedestrian volume;HH_PedMode: Unknown;PCol_04: Unknown;PCol_Rate: Unknown; abstract: | A. PURPOSE | This dataset is created to show the estimated yearly pedestrian volume at each intersection. | B. METHODOLOGY | http://archives.sfmta.com/cms/rpedmast/documents/FinalPedestrianCountReport6_17_11.pdf | C. UPDATE FREQUENCY | Not updated | D. OTHER CRITICAL INFO | Volume estimates made with 2011 transportation data and 2000 US Census data | E. ATTRIBUTES | CNN: San Francisco's street centerline network unique ID; ST_NAME1: Name of cross street;ST_TYPE1: Type of street;ST_NAME2: Name of cross street;ST_TYPE2: Type of street;ST_NAME3: Name of cross street;ST_TYPE3: Type of street;ST_NAME4: Name of cross street;ST_TYPE4: Type of street;TOTEMP2: Total number of jobs within 0.25 miles of the intersection in 2010. Data calculated by SFCTA from SFCTA traffic analysis zones. These data are produced by the SF Planning Department by allocating ABAG countylevel land use figures to the SFCTA's 981 transportation analysis zones within San Francisco;UNIVPROX: Intersection is located within 0.25 miles of one the five major university campuses in the city: USF Lone Mountain, UCSF Parnassus, UCSF Mission Bay, City College Ingleside, SFSU Park Merced. Other schools are not included, since they are either smaller, more spread out, or different in character (e.g., serve adult/commuter students at night). (1 = yes, 0 = no);Signalized: Intersection is controlled by a traffic signal. (1 = yes, 0 = no); PkgMeters: Intersection is in a zone with parking meters (e.g., parking meters are present on at least one approach to the intersection). (1 = yes, 0 =no); MaxPctSlpe: Maximum slope of any approach to the intersection. (Percent slope); Model6_Vol: Annual pedestrian volume;HH_PedMode: Unknown;PCol_04: Unknown;PCol_Rate: Unknown

  19. Projections 2040 by County: Female Population by Age

    • opendata.mtc.ca.gov
    • hub.arcgis.com
    • +1more
    Updated Jul 17, 2019
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    ABAG/MTC (2019). Projections 2040 by County: Female Population by Age [Dataset]. https://opendata.mtc.ca.gov/datasets/projections-2040-by-county-female-population-by-age/geoservice
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    Dataset updated
    Jul 17, 2019
    Dataset provided by
    Association of Bay Area Governmentshttps://abag.ca.gov/
    Authors
    ABAG/MTC
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This feature set contains female population projections, by age, from Projections 2040 for the San Francisco Bay Region. This forecast represents female population projections resulting from Plan Bay Area 2040. Numbers are provided by county. Female population numbers are included for 2010 (two versions), 2015, 2020, 2025, 2030, 2035, and 2040. For 2010, two data points are provided:A tabulation (base year A) from the 2010 model simulation (base year A); and(Preferred) A tabulation (base year B) from the 2010 pre-run microdata, designed to approximate (but may still differ from) Census 2010 counts.Projection data is included for female population for the following age ranges: 0-4 (under 5), 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, 80-84, and 85+ (85 and over).This feature set was assembled using unclipped county features. For those who prefer Projections 2040 data using county features with ocean and bay waters clipped out, the data in this feature service can be joined to San Francisco Bay Region Counties (clipped).Other Projections 2040 feature sets:Households and population per countyHouseholds and population per jurisdiction (incorporated place and unincorporated county)Households and population per Census TractJobs and employment per countyJobs and employment per jurisdiction (incorporated place and unincorporated county)Jobs per Census TractFemale population, by age range, per jurisdiction (incorporated place and unincorporated county)Male population, by age range, per countyMale population, by age range, per jurisdiction (incorporated place and unincorporated county)Total population, by age range, per countyTotal population, by age range, per jurisdiction (incorporated place and unincorporated county)

  20. 2014 10: Bay Area Suburbanization of Poverty, 2000 to 2012

    • opendata.mtc.ca.gov
    • hub.arcgis.com
    Updated Oct 22, 2014
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    MTC/ABAG (2014). 2014 10: Bay Area Suburbanization of Poverty, 2000 to 2012 [Dataset]. https://opendata.mtc.ca.gov/documents/cdca2755936549b8a68531883d60ae3a
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    Dataset updated
    Oct 22, 2014
    Dataset provided by
    Metropolitan Transportation Commission
    Association of Bay Area Governmentshttps://abag.ca.gov/
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    San Francisco Bay Area
    Description

    Place types were defined by grouping United States Census Designated Places as Central Cities, Inner Suburbs, Outer Suburbs, and Balance of Counties for the San Francisco Bay Region, based on their population, employment and travel characteristics.Viewed regionally, the percentage increase in poverty was highest in the Outer Suburbs (62% regional average), as compared to the Central Cities (22% regional average) and Inner Suburbs (24% regional average) showing a pattern of larger increases in poverty in the Region's periphery. The percentage increases in poverty in the Outer Suburbs by County range from 38% to 89%, as compared to the Inner Suburbs which range from 17% to 30% and Central Cities from 3% to 40%.

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MTC/ABAG (2021). San Francisco Bay Region Counties (clipped) [Dataset]. https://opendata-mtc.opendata.arcgis.com/datasets/15e88533ab3c488a853ed32a438ad4c4
Organization logoOrganization logo

San Francisco Bay Region Counties (clipped)

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Dataset updated
Nov 3, 2021
Dataset provided by
Association of Bay Area Governmentshttps://abag.ca.gov/
Metropolitan Transportation Commission
Authors
MTC/ABAG
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Area covered
Description

County boundaries for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from, and clipped using, California 2020 TIGER/Line shapefiles by the Metropolitan Transportation Commission. The 2020 TIGER/Line Shapefiles reflect available governmental unit boundaries of the counties and equivalent entities as of May 28, 2021.Counties and equivalent entities are primary legal divisions of states. In most states, these entities are termed “counties.” Each county or statistically equivalent entity is assigned a 3-character FIPS code that is unique within a state.

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