The population density of San Antonio, TX was 2,799 in 2010.

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.

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Geographic and Population Datasets Involving San Antonio, TX

  • API

    CPI 1.1 Texas Child Population (ages 0-17) by County - 2010 - 2019

    data.texas.gov | Last Updated 2020-06-26T23:41:11.000Z

    Current population estimates and projections for all years from 2010 to 2019 as of December 2019. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Visit dfps.state.tx.us for information on all DFPS programs.

  • API

    CPI 1.1 Texas Child Population (ages 0-17) by Region - 2010- 2019

    data.texas.gov | Last Updated 2020-06-26T23:44:03.000Z

    Current population estimates and projections for all years from 2010 to 2019 as of December 2019. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Visit dfps.state.tx.us for information on all DFPS programs

  • API

    APS 1.1 Texas Adult Populations at Risk: County FY2010-FY2019

    data.texas.gov | Last Updated 2020-06-26T23:42:05.000Z

    APS investigates allegations of abuse, neglect, and financial exploitation and provides protective services, regardless of race, creed, color, or national origin to people who are: • age 65 or older; • age 18-64 with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection; or • emancipated minors with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection. APS clients do not have to meet financial eligibility requirements. The population totals will not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Population, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections for all years from 2010 to 2019 as of December 2019.

  • API

    APS 1.1 Texas Adult Populations at Risk by Region - FY2010-FY2019

    data.texas.gov | Last Updated 2020-06-26T23:41:52.000Z

    APS investigates allegations of abuse, neglect, and financial exploitation and provides protective services, regardless of race, creed, color, or national origin to people who are: • age 65 or older; • age 18-64 with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection; or • emancipated minors with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection. APS clients do not have to meet financial eligibility requirements. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Population, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections for all years from 2010 to 2019 as of December 2019.

  • API

    CPS 2.4 Children In Legal Responsibility on August 31 by Legal Status and Average Days in Care FY2010-2019

    data.texas.gov | Last Updated 2020-06-26T23:43:53.000Z

    Children in DFPS custody are those for whom a court has appointed DFPS legal responsibility through temporary or permanent managing conservatorship or other court ordered legal basis. This chart includes any child in DFPS custody on August 31 of the fiscal year. A description of the different types of legal statuses is in the CPS glossary: http://www.dfps.state.tx.us/About_DFPS/Data_Book/Child_Protective_Services/Resources/glossary.asp Visit dfps.state.tx.us for information on Children In Legal Responsibility and all DFPS programs.

  • API

    AMS San Diego Testbed - Calibration Data

    datahub.transportation.gov | Last Updated 2020-06-23T04:09:50.000Z

    The data in this repository were collected from the San Diego, California testbed, namely, I-15 from the interchange with SR-78 in the north to the interchange with SR-163 in the south, along the mainline and at the entrance ramps. This file contains information on the field observation and simulation results for speed profile from the Dallas, Texas testbed. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.

  • API

    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

  • API

    Noaansf Ecohab Heterosigma Ctd

    noaa-fisheries-nwfsc.data.socrata.com | Last Updated 2017-06-05T22:59:14.000Z

    InPort Dataset ID: 17794 InPort Entity ID: 36788 Over one half of the worlds fish production for human consumption currently comes from aquaculture, while wild fisheries yields are either stable or declining. Recurring threats from the raphidophyte, Heterosigma akashiwo Hada (Sournia) have caused extensive damage ($2-6 million per episode) to wild and net-penned fish of Puget Sound, Washington, and are believed to be increasing in scope and magnitude in this region, and elsewhere in the world over the past two decades. The mechanism of H. akashiwo toxicity is not well understood. The toxic activity of H. akashiwo has been attributed to the production of reactive oxygen species, brevetoxin-like compound(s), excessive mucus, or hemolytic activity; however these mechanisms are not confirmed consistently in all fish-killing events or cultured strains. The difficulty of conducting research with active, toxin-producing field populations of H. akashiwo have resulted in conflicting findings from those obtained in lab culture studies, thereby limiting the ability of fish farmers to respond to these episodic blooms. Collaborators in this project are: Vera Trainer (NWFSC), William Cochlan (San Francisco State University), Charles Trick (University of Western Ontario), and Mark Wells (University of Maine). The overall goal of this project is to identify the primary toxic element and the specific environmental factors that stimulate fish-killing H. akashiwo blooms, and thereby provide managers with the fundamental tools needed to help reduce the frequency and toxic magnitude of these harmful algal events. Studies to date have provided incomplete and conflicting observations on the mode of toxicity and the environmental stimulation of toxification. We propose a three-pronged approach to study the environmental controls of H. akashiwo growth and toxin production; laboratory culture experiments, field observations, and bottle and mesocosm manipulation experiments.The project objectives are to: 1. identify the element(s) of toxic activity (inorganic, organic, or synergistic) associated with blooms of H. akashiwo and the various cellular morphologies of this alga, 2. determine the environmental parameters that stimulate the growth success and expression of cell toxicity in the H. akashiwo populations of Puget Sound. Because previous studies have used H. akashiwo cultures with little or no toxic activity, our approach is to use a living laboratory to study H. akashiwo bloom ecology and toxicity using natural assemblages. Using a mobile lab at field sites where H. akashiwo cells are regularly found will enable us to fully characterize the toxic element(s) responsible for fish mortality, and the environmental factors influencing toxicity. Findings from annual field studies in June and two rapid response deployments during major bloom events will be confirmed using laboratory studies with fresh ( 6 mo. old) isolates. The expected results are: 1. determination of the key elements of toxicity of H. akashiwo, 2. characterization of the environmental variables that influence either the induction or depression of elements of toxic activity in H. akashiwo, 3. characterization of environmentally-induced metabolites corresponding to condition of toxin production (metabolomics) and 4. design of a strategy for realistic mitigation of H. akashiwo activities in Puget Sound, Washington. This is a stand-alone project funded for 3 years through the NOAA/NSF ECOHAB program.