The population density of Rancho Santa Margarita, CA was 3,766 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 Rancho Santa Margarita, CA

  • API

    T12 Emergency Resp Times Fire

    data.sustainablesm.org | Last Updated 2020-01-17T16:58:05.000Z

    Fire service standards are established by the National Fire Protection Agency (NFPA); NFPA Standard 1710 addresses the performance measure of travel time and sets its standards by percentiles rather than averages. According to NFPA 1710: The fire department’s fire suppression resources shall be deployed to provide for the arrival of an engine company within a 240-second travel time to 90 percent of the incidents; in 2014 SMFD responded to 70% of the incidents within a 240-second travel time. When considering travel time, it is important to understand that travel time is affected by population density, traffic, construction zones, street closures, etc.

  • 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

    Vital Signs: Migration - Bay Area

    data.bayareametro.gov | Last Updated 2019-10-25T20:40:04.000Z

    VITAL SIGNS INDICATOR Migration (EQ4) FULL MEASURE NAME Migration flows LAST UPDATED December 2018 DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables. DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration. Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23) One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.

  • API

    Urbanized Areas (2018)

    data.bayareametro.gov | Last Updated 2020-12-08T21:16:05.000Z

    Urban footprint for the San Francisco Bay Region and its surrounding counties in 2018. The California Department of Conservation Farmland Mapping and Monitoring Program (FMMP) completely updates this data every ten years. Between the decennial releases there are three intermediary, partial updates that occur every two years. The next full release, where every mapped county has been updated, will be sometime in 2020. Information on the Farmland Mapping and Monitoring Program can be found at https://www.conservation.ca.gov/dlrp/fmmp/. Data for all areas, except the City and County of San Francisco, were extracted from a cumulative feature set composed of FMMP releases from 2010 to 2018 by selecting the Urban and Built-up Land category. Counties that have yet to be updated, this is the third update for this cycle, are from 2010. The City and County of San Francisco (San Francisco) is not part of the FMMP data because its level of urbanization does not allow for agricultural uses that meet the ten acre minimum requirement. Features for San Francisco, including Treasure Island/Yerba Buena Island and Alcatraz Island, were created by the Metropolitan Transportation Commission (MTC) using TomTom 2019 data. Water features for San Francisco Bay and the Pacific Ocean were used to erase water areas from the county feature, leaving the land areas. Undeveloped islands remaining after the erase function (Farallon Islands and Seal Rocks) were deleted, leaving only the urbanized areas. To make San Francisco's urbanized area along the coast consistent with the FMMP data, MTC staff deleted the beach areas and open space between the Pacific Ocean and Skyline Boulevard, Great Highway, and Lincoln Boulevard using the approach used by the FMMP along the San Mateo County coast. As the land area of San Francisco was fully urbanized by the time the FMMP began in 1984, these features were added to the 2018 Urban Footprint update to complete the urbanized area coverage for the region. FMMP data was chosen over Census Urban Area/Urban Cluster data to represent the region's urban footprint because of its consistent areal representation and update frequency. FMMP defines Urban and Built-up Land as "Land occupied by structures with a building density of at least 1 unit to 1.5 acres, or approximately 6 structures to a 10-acre parcel. (editor note - parcel in this sense represents a general area of land, not geographies created by Assessors for tax purposes) This land is used for residential, industrial, commercial, construction, institutional, public administration, railroad and other transportation yards, cemeteries, airports, golf courses, sanitary landfills, sewage treatment, water control structures, and other developed purposes." This definition that has remained consistent since the beginning of the program. The Department of Conservation has always mapped FMMP categories at a minimum mapping unit of 10 acres. This has the added benefit that it captures developed areas that do not meet the 2,500 person minimum required by the Census. While not all California counties are included in FMMP data, every county in the region, except San Francisco, has been included in the dataset since it was first produced in 1984. As mentioned above, San Francisco was already fully urbanized by the time the FMMP began so including its area from another source does not violate the intent of the mapping program. In contrast, Census Urban Areas/Urban Clusters are based on block geographies which are updated every 10 years. In an example of how this can distort areas identified as urban, the 2000 release showed a significant increase in urban area west of Santa Rosa compared to what was there in 1990. Then, most of that perceived increase in area no longer existed in the 2010 release as blocks were redrawn because discrete pockets were able to meet population densities that triggered change. This makes direct comparisons between Urban Area releases more difficult than th