VITAL SIGNS INDICATOR

Population (LU1)

FULL MEASURE NAME

Population estimates

LAST UPDATED

February 2023

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 SOURCE

California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

Table E-6: County Population Estimates (1960-1970)

Table E-4: Population Estimates for Counties and State (1970-2021)

Table E-8: Historical Population and Housing Estimates (1990-2010)

Table E-5: Population and Housing Estimates (2010-2021)

Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs

Computed using 2020 US Census TIGER boundaries

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

1970-2020

U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/

2011-2021

Form B01003

Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about

CONTACT INFORMATION

vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)

All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. 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 December 2022.

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 (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).

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

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

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

This feature set contains total population (male and female), by age, projections from Projections 2040 for the San Francisco Bay Region. This forecast represents total population projections resulting from Plan Bay Area 2040. Numbers are provided by county. Total 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 total population for the following age ranges: 0-4 (under 5), 5-19, 20-44, 45-64, and 65+ (65 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 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 jurisdiction (incorporated place and unincorporated county)

This feature set contains male population projections, by age, from Projections 2040 for the San Francisco Bay Region. This forecast represents male population projections resulting from Plan Bay Area 2040. Numbers are provided by county. Male 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 male 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 countyFemale population, by age range, per jurisdiction (incorporated place and unincorporated county)Male 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)

This feature set contains household and population projections from Projections 2040 for the San Francisco Bay Region. This forecast represents household and population projections resulting from Plan Bay Area 2040. Numbers are provided by county. Household and 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 total households, group quarter population, household population, persons per household, and total population.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 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 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)

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 California 2020 TIGER/Line shapefile 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.

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)

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.

U.S. Census Bureau QuickFacts statistics for Bay County, Florida. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and Zip codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential Zip code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the Zip code-level life expectancy calculation, it is assumed that postal Zip codes share the same boundaries as Zip Code Census Tabulation Areas (ZCTAs). More information on the relationship between Zip codes and ZCTAs can be found at https://www.census.gov/geo/reference/zctas.html. Zip code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 Zip code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for Zip codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest Zip code with population. Zip code population for 2000 estimates comes from the Decennial Census. Zip code population for 2013 estimates are from the American Community Survey (5-Year Average). The ACS provides Zip code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to Zip codes based on majority land-area.

Zip codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, Zip codes with populations of less than 5,000 were aggregated with neighboring Zip codes until the merged areas had a population of more than 5,000. In this way, the original 305 Bay Area Zip codes were reduced to 218 Zip code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

Daily Miles Traveled (T14)

FULL MEASURE NAME

Total vehicle miles traveled

LAST UPDATED

August 2022

DESCRIPTION

Daily miles traveled, commonly referred to as vehicle miles traveled (VMT), reflects the total and per-person number of miles traveled in personal vehicles on a typical weekday. The dataset includes metropolitan area, regional and county tables for total vehicle miles traveled.

DATA SOURCE

California Department of Transportation: California Public Road Data/Highway Performance Monitoring System - http://www.dot.ca.gov/hq/tsip/hpms/datalibrary.php

2001-2020

Federal Highway Administration: Highway Statistics - https://www.fhwa.dot.gov/policyinformation/statistics/2020/hm71.cfm

2020

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/

2001-2020

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html

2020

CONTACT INFORMATION

vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)

Vehicle miles traveled (VMT) reflects the mileage accrued within the county and not necessarily the residents of that county; even though most trips are due to local residents, additional VMT can be accrued by through-trips. City data was thus discarded due to this limitation and the analysis only examines county and regional data, where through-trips are generally less common.

The metropolitan area comparison was performed by summing all of the urbanized areas for which the majority of its population falls within a given metropolitan area (9-county region for the San Francisco Bay Area and the primary metropolitan statistical area (MSA) for all others). For the metro analysis, no VMT data is available in rural areas; it is only available for intraregional analysis purposes. VMT per capita is calculated by dividing VMT by an estimate of the traveling population.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Forecasts for Year 2010 through 2040 containing values for Households by Inc. Quartile; Households; Jobs; Population by Gender, Age; Units; Employed Residents; Population by Age; Population for Priority Development Areas (PDAs) in the nine county San Francisco Bay Area region.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

A dataset listing Florida counties by population for 2024.

U.S. Census Bureau QuickFacts statistics for Discovery Bay CDP, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

U.S. Census Bureau QuickFacts statistics for Half Moon Bay city, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

VITAL SIGNS INDICATOR

Transit Ridership (T11)

FULL MEASURE NAME

Daily transit boardings

LAST UPDATED

February 2023

DESCRIPTION

Transit ridership refers to the number of passenger boardings on public transportation, which includes buses, rail systems and ferries. The dataset includes metropolitan area, regional, mode and operator tables for total typical weekday boardings.

DATA SOURCE

Federal Transit Administration: National Transit Database - http://www.ntdprogram.gov/ntdprogram/data.htm

1991-2022

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/

1991-2022

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html

1991-2022

CONTACT INFORMATION

vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)

The National Transit Database (NTD) dataset was lightly cleaned to correct for erroneous zero values - in which null values (unsubmitted data) were incorrectly marked as zeroes. Paratransit data is sparse in early years of the NTD dataset, meaning that transit ridership estimates in the early 1990s are likely underestimated. Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD.

2022 data should be considered preliminary, as it comes from the monthly data tables rather than the longer-term time series dataset. Weekday ridership is calculated by taking the total annual ridership and dividing by 300, an assumption which is consistent with MTC travel modeling procedures; it was also compared to observed weekday boarding data (which is more limited in availability) to ensure consistency on the regional level. Per-capita transit ridership is calculated for the operator's general service area or taxation district; for example, BART includes the three core counties (San Francisco, Alameda, and Contra Costa), as well as northern San Mateo County post-SFO extension, and AC Transit includes the cities located within its service area. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

U.S. Census Bureau QuickFacts statistics for Morro Bay city, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

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.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Forecasts for Year 2010 through 2040 containing values for Households by Inc. Quartile; Households; Jobs; Population by Gender, Age; Units; Employed Residents; Population by Age; Population for jurisdictions in the nine county San Francisco Bay Area region.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.