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

Chart and table of population level and growth rate for the San Francisco metro area from 1950 to 2025.

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 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

In 2023, the population of the San Francisco-Oakland-Berkeley metropolitan area in the United States was about 4.57 million people. This is a slight decrease from the previous year, when the population was about 4.58 million people.

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.

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)

INTRODUCTION: As California’s homeless population continues to grow at an alarming rate, large metropolitan regions like the San Francisco Bay Area face unique challenges in coordinating efforts to track and improve homelessness. As an interconnected region of nine counties with diverse community needs, identifying homeless population trends across San Francisco Bay Area counties can help direct efforts more effectively throughout the region, and inform initiatives to improve homelessness at the city, county, and metropolitan level. OBJECTIVES: The primary objective of this research is to compare the annual Point-in-Time (PIT) counts of homelessness across San Francisco Bay Area counties between the years 2018-2022. The secondary objective of this research is to compare the annual Point-in-Time (PIT) counts of homelessness among different age groups in each of the nine San Francisco Bay Area counties between the years 2018-2022. METHODS: Two datasets were used to conduct research. The first dataset (Dataset 1) contains Point-in-Time (PIT) homeless counts published by the U.S. Department of Housing and Urban Development. Dataset 1 was cleaned using Microsoft Excel and uploaded to Tableau Desktop Public Edition 2022.4.1 as a CSV file. The second dataset (Dataset 2) was published by Data SF and contains shapefiles of geographic boundaries of San Francisco Bay Area counties. Both datasets were joined in Tableau Desktop Public Edition 2022.4 and all data analysis was conducted using Tableau visualizations in the form of bar charts, highlight tables, and maps. RESULTS: Alameda, San Francisco, and Santa Clara counties consistently reported the highest annual count of people experiencing homelessness across all 5 years between 2018-2022. Alameda, Napa, and San Mateo counties showed the largest increase in homelessness between 2018 and 2022. Alameda County showed a significant increase in homeless individuals under the age of 18. CONCLUSIONS: Results from this research reveal both stark and fluctuating differences in homeless counts among San Francisco Bay Area Counties over time, suggesting that a regional approach that focuses on collaboration across counties and coordination of services could prove beneficial for improving homelessness throughout the region. Results suggest that more immediate efforts to improve homelessness should focus on the counties of Alameda, San Francisco, Santa Clara, and San Mateo. Changes in homelessness during the COVID-19 pandemic years of 2020-2022 point to an urgent need to support Contra Costa County.

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)

This polygon shapefile contains superdistrict boundaries and population statistics created by the Metropolitan Transportation Comission (MTC) using Census 2000 data. Superdistricts are used in the analysis of sub-county level demographic and travel forecasts. MTC maintains a set of regional travel analysis zones for use in MTC planning studies. These travel analysis zones (TAZs) are typically small area neighborhoods or communities that serve as the smallest geographic basis for travel demand model forecasting systems. From time to time, MTC updates the regional travel analysis zone system to reflect changes in decennial census geography, changes in computing capability, and forecasting needs for particular corridor studies. In addition to regional TAZs and counties, MTC supports an intermediate geographic scale, "superdistricts," for analysis and reporting purposes. There are 34 superdistricts in the nine-county Bay Area. This layer is part of the Bay Area Metropolitan Transportation Commission (MTC) GIS Maps and Data collection.

According to population estimates recently released by the California Department of Housing and Community Development, the San Francisco Bay Region is the fastest growing region in the state.San Jose, followed by San Francisco and Oakland have the highest populations in the region, and three bay area cities made the top 10 ranking. In addition, our region also has 4 counties; Santa Clara (1), Alameda (2), San Francisco (5) and San Mateo (9), in the top 10 fastest growing counties. Dublin (3), Campbell (7) and Rio Vista (8) each had a significant percentage change in their population growth. The state data reports population and housing trends for 482 California cities. Last year, all but 43 cities saw an increase in residents, with the declines typically experienced in the state's rural areas.

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.

Chart and table of population level and growth rate for the San Jose metro area from 1950 to 2025.

Abstract

The Greater Bay Area Cancer Registry (GBACR), in compliance with California state law, gathers information about all cancers diagnosed or treated in a nine-county area (Alameda, Contra Costa, Marin, Monterey, San Benito, San Francisco, San Mateo, Santa...

Documentation

PHS does NOT host these data. This listing is information only.

The Greater Bay Area Cancer Registry (GBACR), in compliance with California state law, gathers information about all cancers diagnosed or treated in a nine-county area (Alameda, Contra Costa, Marin, Monterey, San Benito, San Francisco, San Mateo, Santa Clara and Santa Cruz). This information is obtained from medical records provided by hospitals, doctors\342\200\231 offices, and other related facilities.

The information, stored under secure conditions with strict regulations that protect confidentiality, helps the GBACR understand cancer occurrence and survival in the Greater Bay Area. For each patient, the information includes basic demographic facts like age, gender, and race/ethnicity, as well as cancer type, extent of disease, treatment and survival. Combined over the diverse Bay Area population, this information gives the GBACR and all users an opportunity to learn how such characteristics may be related to cancer causes, mortality, care and prevention.

In addition to its local use, information collected by the GBACR becomes part of state and federal population-based registries whose mission is to monitor cancer occurrence at the state and national levels, respectively. Data from the GBACR have contributed to the National Cancer Institute’s Surveillance, Epidemiology and End Results (SEER) program since 1973. The nine counties are also part of the statewide California Cancer Registry (CCR), which conducts essential monitoring of cancer occurrence and survival in California.

GBACR data are of the highest quality, as recognized by national and international registry standard-setting organizations, including SEER, the National Program for Cancer Registries, and the North American Association for Central Cancer Registries (NAACCR).

The CPIC has also started collecting data on environmenal factors. These data are available in the The California Neighborhoods Data System. This a new resource for examining the impact of neighborhood characteristics on cancer incidence and outcomes in populations includes a compilation of existing geospatial and other secondary data for characterizing contextual factors

A summary and description of social and built environment data and measures in the California Neighborhoods Data System (2010) can be found here: Social and Built Environment Data and Measures

More information about this new data source can be found here: The California Neighborhoods Data System

Patient characteristics All reported cancer cases in the state of California.

Data overview Data categories Socioeconomic status Racial/ethnic composition Immigration/acculturation characteristics Racial/ethnic residential segregation Population density Urbanicity (Rural/Urban) Housing Businesses Commuting Street connectivity Parks Farmers Markets Traffic density Crime Tapestry Segmentation

Notes To apply for these data, you can see instructions here: https://www.ccrcal.org/retrieve-data/data-for-researchers/how-to-request-ccr-data/

VITAL SIGNS INDICATOR
Housing Production (LU4)

FULL MEASURE NAME
Produced housing units by unit type

LAST UPDATED
February 2023

DESCRIPTION
Housing production is measured in terms of the number of units that local jurisdictions produces throughout a given year. The annual production count captures housing units added by new construction and annexations, subtracts demolitions and destruction from natural disasters, and adjusts for units lost or gained by conversions.

DATA SOURCE
California Department of Finance, Form E-8 - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/
1990-2010

California Department of Finance, Form E-5 - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/
2011-2022

U.S. Census Bureau Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Single-family housing units include single detached units and single attached units. Multi-family housing includes two to four units and five plus or apartment units.

Housing production data for the region, counties, and cities for each year is the difference of annual housing unit estimates from the California Department of Finance. Housing production data for metropolitan areas for each year is the difference of annual housing unit estimates from the Census Bureau’s Population Estimates Program. CA Department of Finance data uses an annual cycle between January 1 and December 31, whereas U.S. Census Bureau data uses an annual cycle from April 1 to March 31 of the following year.

VITAL SIGNS INDICATOR Income (EC4)

FULL MEASURE NAME Household income by place of residence

LAST UPDATED May 2019

DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org

U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.

Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

Table of household forecast numbers from Plan Bay Area 2040 for the San Francisco Bay Region. Household 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 Household 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 HouseholdsNumber of Households in Lowest Income QuartileNumber of Households in Second Lowest Income QuartileNumber of Households in Second highest Income QuartileNumber of Households in Highest Income QuartileOther 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)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)Population and Demographics (total population, household and group quarter populations, population by age group, share of population that is 62+, high school enrollment, and college enrollment)

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.

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.

Transportation Analysis Zones (TAZs) are used in the Metropolitan Transportation Commission travel and Urban Sim models for the San Francisco Bay Region. These models are used in processes to forecast population growth, economic growth, and transportation/transit capacity and responsiveness and then distribute those results throughout the region.Data tables containing modeling results are joined to the TAZ features using a zone id (taz1454). Tables currently available for download are as follows:Plan Bay Area 2040 ForecastEmployment (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)Population and Demographics (total population, household and group quarter populations, population by age group, share of population that is 62+, high school enrollment, and college enrollment)

U.S. Census Bureau QuickFacts statistics for Bay Point 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.