The population density of San Francisco, CA was 18,562 in 2018. The population density of San Jose, CA was 5,816 in 2018.

Population Density

Population Density is computed by dividing the total population by Land Area Per Square Mile.

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Geographic and Population Datasets Involving San Jose, CA or San Francisco, CA

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    San Mateo County And California Crime Rates 2000-2014

    performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000Z

    Violent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.

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    Next Generation Simulation (NGSIM) Vehicle Trajectories and Supporting Data

    datahub.transportation.gov | Last Updated 2020-06-22T19:15:56.000Z

    Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset.

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    Housing Affordability Index- California and San Mateo County

    performance.smcgov.org | Last Updated 2016-07-27T18:20:08.000Z

    URL, CA Association of Realtors,

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    COVID-19 Cases and Deaths Summarized by Geography

    data.sfgov.org | Last Updated 2020-10-20T14:31:56.000Z

    <strong>A. SUMMARY</strong> Medical provider confirmed COVID-19 cases and confirmed COVID-19 related deaths in San Francisco, CA aggregated by several different geographic areas and normalized by 2018 American Community Survey (ACS) 5-year estimates for population data to calculate rate per 10,000 residents. Cases and deaths are both mapped to the residence of the individual, not to where they were infected or died. For example, if one was infected in San Francisco at work but lives in the East Bay, those are not counted as SF Cases or if one dies in Zuckerberg San Francisco General but is from another county, that is also not counted in this dataset. Dataset is cumulative and covers cases going back to March 2nd, 2020 when testing began. It is updated daily. Geographic areas summarized are: 1. <a href="https://data.sfgov.org/Geographic-Locations-and-Boundaries/Analysis-Neighborhoods/p5b7-5n3h">Analysis Neighborhoods</a> 2. <a href="https://data.sfgov.org/Geographic-Locations-and-Boundaries/Census-2010-Tracts-for-San-Francisco/rarb-5ahf">Census Tracts</a> 3. <a href="https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html">Census Zip Code Tabulation Areas</a> <strong>B. HOW THE DATASET IS CREATED</strong> Addresses from medical data are geocoded by the San Francisco Department of Public Health (SFDPH). Those addresses are spatially joined to the geographic areas. Counts are generated based on the number of address points that match each geographic area. The 2018 ACS estimates for population provided by the Census are used to create a rate which is equal to ([count] / [acs_population]) * 10000) representing the number of cases per 10,000 residents. <strong>C. UPDATE PROCESS</strong> Geographic analysis is scripted by SFDPH staff and synced to this dataset each day. <strong>D. HOW TO USE THIS DATASET</strong> <em>Privacy rules in effect</em> To protect privacy, certain rules are in effect: 1. Case counts greater than 0 and less than 10 are dropped - these will be null (blank) values 2. Death counts greater than 0 and less than 10 are dropped - these will be null (blank) values 3. Cases and deaths dropped altogether for areas where acs_population < 1000 <em>Rate suppression in effect where counts lower than 20</em> Rates are not calculated unless the case count is greater than or equal to 20. Rates are generally unstable at small numbers, so we avoid calculating them directly. We advise you to apply the same approach as this is best practice in epidemiology. <em>A note on Census ZIP Code Tabulation Areas (ZCTAs)</em> ZIP Code Tabulation Areas are special boundaries created by the U.S. Census based on ZIP Codes developed by the USPS. They are not, however, the same thing. ZCTAs are areal representations of routes. <a href="https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html">Read how the Census develops ZCTAs on their website</a>. <em>Row included for Citywide case counts, incidence rate, and deaths</em> A single row is included that has the Citywide case counts and incidence rate. This can be used for comparisons. Citywide will capture all cases regardless of address quality. While some cases cannot be mapped to sub-areas like Census Tracts, ongoing data quality efforts result in improved mapping on a rolling bases.

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    Health_5510B_Covered California Enrollment_HCU3

    datahub.smcgov.org | Last Updated 2020-01-16T20:57:24.000Z

    number of San Mateo County residents in Covered CA

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    County/Metro Indicator - Diabetes

    healthstat.dph.sbcounty.gov | Last Updated 2019-02-13T18:18:45.000Z

    UCLA Center for Health Policy Research. AskCHIS 2003, 2005, 2007, 2009, 2011-2017. Ever diagnosed with diabetes (San Bernardino County, State of California). Available at ask.chis.ucla.edu. Exported on February 13, 2019.

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    Vital Signs: Population – by region shares

    data.bayareametro.gov | Last Updated 2018-07-06T18:06:55.000Z

    VITAL SIGNS INDICATOR Population (LU1) FULL MEASURE NAME Population estimates LAST UPDATED September 2016 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 1960-1990 Decennial Census http://factfinder2.census.gov California Department of Finance 1961-2016 Population and Housing Estimates http://www.dof.ca.gov/research/demographic/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, 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 infill 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 as current as July 2016. Population estimates for PDAs were derived from Census population counts at the block group level for 2000-2014 and at the tract level for 1970-1990. 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). 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. Estimates of density for tracts and 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 InlandCoastalDelta: American Canyon, Benicia, Clayton, Concord, Cotati, Danville, Dublin, Lafayette, Martinez, Moraga, Napa, Novato, Orinda, Petaluma, Pleasant Hill, Pleasanton, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Walnut Creek, Antioch, Brentwood, Calistoga, Cloverdale, Dixon, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Livermore, Morgan Hill, Oakley, Pittsburg, Rio Vista, Sonoma, St. Helena, Suisun City, Vacaville, Windsor, Yountville Unincorporated: all unincorporated towns

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    County/Metro Indicator - Source of Health Care (Archive)

    data.communityvitalsigns.org | Last Updated 2019-02-06T15:56:58.000Z

    UCLA Center for Health Policy Research. AskCHIS 2001, 2003, 2005, 2007, 2009, 2011-2017. Have usual place to go to when sick or need health advice (San Bernardino County, State of California). Available at ask.chis.ucla.edu. Exported on February 05, 2019.

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    Vital Signs: Jobs – by subcounty

    data.bayareametro.gov | Last Updated 2020-04-13T23:19:44.000Z

    VITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED March 2020 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/ U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/ U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/ Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/ METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

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    County/Metro Indicator - Asthma

    healthstat.dph.sbcounty.gov | Last Updated 2019-03-14T15:24:43.000Z

    UCLA Center for Health Policy Research. AskCHIS 2001, 2003, 2005, 2007, 2009, 2011-2016. Ever diagnosed with asthma (San Bernardino County, State of California). Available at ask.chis.ucla.edu. Exported on March 14th, 2019.