The population density of Hacienda Heights, CA was 4,938 in 2014. The population density of Monterey Park, CA was 7,947 in 2014.

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:

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Geographic and Population Datasets Involving Monterey Park, CA or Hacienda Heights, CA

  • API

    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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    MCAH Birth File

    data.countyofnapa.org | Last Updated 2024-02-07T17:45:49.000Z

    Data Source: CA Department of Public Health, Maternal Child and Adolescent Health Division This data biography includes information about who created this data, and how, where, when, and why it was collected. We, the epidemiology team at Napa County Health and Human Services Agency, Public Health Division, created it to help you understand where the data we analyze, and share comes from. If you have any further questions, we can be reached at epidemiology@countyofnapa.org. How was the data collected? This data product is the result of the merging of two data files spanning different time periods. The California Birth Statistical Master File from 2007 to 2017 and the California Comprehensive Master Birth File from 2018 to 2021 that replaced the Master File. Additional metrics were included from the calculations off the source datasets. Population Density data from the US Census Bureau American Community Survey 5-year estimates: Poverty States in the past 12 months & Population density data from the California Department of Health Care Access and Information: Healthcare Workforce were included as metrics or to calculate new metrics. Who was included and excluded from the data? Birth records from all live births of birthing parent resident of California collected by vital statistics offices throughout the state. Where was the data collected?  Data was collected for all California counties as well as for the state of California. When was the data collected? 2007-2021 Where can I learn more about this data? Data dictionary for the source files used to build the data product can be found here. Detailed definitions assumed for this data product as well as comments on some of the methodologies applied can be found here. For more information overall, please refer to https://www.cdph.ca.gov/Programs/CFH/DMCAH/surveillance/CDPH%20Document%20Library/Data-Dashboards/About-the-Data-Prenatal-Care.pdf.

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    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.

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    HCD Racially Concentrated Areas of Affluence ACS 2019

    data.bayareametro.gov | Last Updated 2023-06-07T00:29:07.000Z

    Racially Concentrated Areas of Affluence (RCAA's) The concept of Racially Concentrated Areas of Affluence (RCAAs) was originally developed by scholars at the University of Minnesota to illustrate the flip side of the Racially and Ethnically Concentrated Areas of Poverty (R/ECAPs) metric used by the California Department of Housing and Community Development (HCD) in the 2015 Affirmatively Furthering Fair Housing (AFFH) rule to more fully tell the story of segregation in the United States. As stated in HCD’s AFFH Guidance Memo, when analyzing patterns and trends of segregation and proposing policy approaches in the Housing Element, localities should not only focus on communities of color. Segregation is a continuum, with polarity between race, poverty, and affluence, which can be a direct product of the same policies and practices. To better evaluate these conditions, both sides of the continuum should be considered and compare patterns within the community and across the region. This more holistic approach will better unveil deeply rooted policies and practices and improve identification and prioritization of contributing factors to inform more meaningful actions. HCD has created a new version of the RCAA metric to better reflect California’s relative diversity and regional conditions, and to aid local jurisdictions in their analysis of racially concentrated areas of poverty and affluence pursuant to AB 686 and AB 1304. HCD’s RCAA metric is provided as a resource to be paired with local data and knowledge – jurisdictions are encouraged but not required to use the RCAA layer provided by HCD in their housing element analyses. To develop the RCAA layer, staff first calculated a Location Quotient (LQ) for each California census tract using data from the 2015-2019 American Community Survey data. This LQ represents the percentage of total white population (White Alone, Not Hispanic or Latino) for each census tract compared to the average percentage of total white population for all census tracts in a given Council of Governments' (COG) region. For example, a census tract with a LQ of 1.5 has a percentage of total white population that is 1.5 times higher than the average percentage of total white population in the given COG region. To determine the RCAAs, census tracts with a LQ of more than 1.25 and a median income 1.5 times higher than the COG Area Median Income (AMI) (or 1.5x the State AMI, whichever is lower) were assigned a numeric score of 1 (Is a RCAA). Census tracts that did not meet this criterion were assigned a score of 0 (Not a RCAA). COG AMI was determined by averaging the 2019 ACS established AMI's for each county within the given COG region. 2019 ACS AMI limits can be found here: https://www.census.gov/quickfacts/fact/table/US/PST045219 [census.gov]. State AMI was based on the ACS 2019 California state AMI ($75,235), which can be found here: https://www.census.gov/quickfacts/fact/table/CA/INC110219 [census.gov]. Census tracts with a total population of less than 75 people, in which the census tract was also largely contained within a non-urbanized area such as a park, open space, or airport, were not identified as RCAAs. Data Source: American Community Survey (ACS), 2015-2019 References: Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press. Damiano, T., Hicks, J., & Goetz, E. (2017). Racially Concentrated Areas of Affluence: A Preliminary Investigation. To learn more about R/ECAPs visit: https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/ch4.pdf [huduser.gov] Original data created by HCD, PlaceWorks 2021