The land area of Discovery Bay, CA was 6 in 2009.
Land Area
Water Area
Land area is a measurement providing the size, in square miles, of the land portions of geographic entities for which the Census Bureau tabulates and disseminates data. Area is calculated from the specific boundary recorded for each entity in the Census Bureau's geographic database. Land area is based on current information in the TIGER® data base, calculated for use with Census 2010.
Water Area figures include inland, coastal, Great Lakes, and territorial sea water. Inland water consists of any lake, reservoir, pond, or similar body of water that is recorded in the Census Bureau's geographic database. It also includes any river, creek, canal, stream, or similar feature that is recorded in that database as a two- dimensional feature (rather than as a single line). The portions of the oceans and related large embayments (such as Chesapeake Bay and Puget Sound), the Gulf of Mexico, and the Caribbean Sea that belong to the United States and its territories are classified as coastal and territorial waters; the Great Lakes are treated as a separate water entity. Rivers and bays that empty into these bodies of water are treated as inland water from the point beyond which they are narrower than 1 nautical mile across. Identification of land and inland, coastal, territorial, and Great Lakes waters is for data presentation purposes only and does not necessarily reflect their legal definitions.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Area Datasets Involving Discovery Bay, CA
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San Mateo County And California Crime Rates 2000-2014
performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000ZViolent 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 2024-05-20T18:02:47.000ZClick “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". 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. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf
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Vital Signs: Commute Patterns - Bay Area
data.bayareametro.gov | Last Updated 2020-05-20T21:44:43.000ZVITAL SIGNS INDICATOR Commute Patterns (T5) FULL MEASURE NAME Commute flows between Bay Area counties LAST UPDATED April 2020 DESCRIPTION Commute patterns, more commonly referred to as county-to-county commute flows, reflect the number of individuals traveling within and between various counties for commuting purposes. DATA SOURCE U.S. Census Transportation Planning Package Table A302103 5-Year Average (2012-2016) https://ctpp.transportation.org/2012-2016-5-year-ctpp/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The Census Transportation Planning Package is produced only every five years and relies upon 5-year rolling average data for all data tables. In order to analyze trends related to the Bay Area, commute patterns were evaluated for all interactions between the nine Bay Area counties and for all interactions between other California counties and any Bay Area county. Commute flows between non-California counties and the San Francisco Bay Area were assumed to be negligible.
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San Mateo County and Other Bay Area Counties Annual Unemployment Rate (not seasonally adjusted)
performance.smcgov.org | Last Updated 2021-05-20T16:46:23.000ZSan Mateo County and Other Bay Area Counties Annual Unemployment Rate (not seasonally adjusted) for years 2000-2019 Compared to Marin County, San Francisco County, Santa Clara County, and the State of California. Data is non-preliminary.
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Bikeshare Isochrones: Line Representation of Stations Accessible
data.bts.gov | Last Updated 2024-08-21T20:04:33.000ZDocked bikeshare stations that can be reached traveling via the road network in a given amount of time (10 or 20 minutes) when starting at a specified docking station. Times were calculated using the street network and a travel speed of 10 miles per hour but straight lines are used to represent the docked bikeshare stations that can be reached. Topography is not taken into account but the type of road is taken in account. Visualization available at: https://data.bts.gov/stories/s/8s3h-vvui
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Vital Signs: Traffic Volumes At Regional Gateways - Bay Area
data.bayareametro.gov | Last Updated 2020-05-20T21:54:46.000ZVITAL SIGNS INDICATOR Traffic Volumes at Regional Gateways (T6) FULL MEASURE NAME Daily vehicles along entry/exit points to the Bay Area LAST UPDATED April 2020 DESCRIPTION Traffic volumes at regional gateways refers to the number of vehicles crossing county boundaries on a typical day to enter or exit the nine-county San Francisco Bay Area. DATA SOURCE California Department of Transportation: Annual Traffic Volume Reports http://traffic-counts.dot.ca.gov CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Traffic counts reflect average annual daily traffic (AADT) counts at all state highway gateway points - entry/exit points to the nine-county San Francisco Bay Area. When the county line data was not available in the traffic volume reports, the closest intersection or interchange was used as a proxy for traffic volumes at the county line.
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Vital Signs: Life Expectancy – by ZIP Code
data.bayareametro.gov | Last Updated 2018-07-06T18:05:06.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population. Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly im
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Unemployment Rate - Bay Area (2022) DRAFT
data.bayareametro.gov | Last Updated 2023-06-13T17:54:15.000ZVITAL SIGNS INDICATOR Unemployment (EC3) FULL MEASURE NAME Unemployment rate by residential location LAST UPDATED December 2022 DESCRIPTION Unemployment refers to the share of the labor force – by place of residence – that is not currently employed full-time or part-time. The unemployment rate reflects the strength of the overall employment market. DATA SOURCE California Employment Development Department: Historical Unemployment Rates 1990-2010 Spreadsheet provided by CAEDD California Employment Development Department: Labor Force and Unemployment Rate for California Sub-County Areas - https://data.edd.ca.gov/Labor-Force-and-Unemployment-Rates/Labor-Force-and-Unemployment-Rate-for-California-S/8z4h-2ak6 2010-2022 California Employment Development Department: Local Area Unemployment Statistics (LAUS) - https://data.edd.ca.gov/Labor-Force-and-Unemployment-Rates/Local-Area-Unemployment-Statistics-LAUS-/e6gw-gvii 1990-2022 U.S. Bureau of Labor Statistics: Local Area Unemployment Statistics (LAUS) - https://download.bls.gov/pub/time.series/la 1990-2021 CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Unemployment rates produced by the CA Employment Development Department (EDD) for the region and county levels are not adjusted for seasonality (as they reflect annual data) and are final data (i.e., not preliminary). Unemployment rates produced by U.S. Bureau of Labor Statistics (BLS) for the metro regions are annual and not adjusted for seasonality; they reflect the primary metropolitan statistical area (MSA) for the named region, except for the San Francisco Bay Area which uses the nine-county region. The unemployment rate is calculated based on the number of unemployed persons divided by the total labor force. Note that the unemployment rate can decline or increase as a result of changes in either variable.
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Vital Signs: Migration - Bay Area
data.bayareametro.gov | Last Updated 2019-10-25T20:40:04.000ZVITAL 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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Vital Signs: Traffic Volumes At Regional Gateways – by Gateway
data.bayareametro.gov | Last Updated 2020-05-20T21:40:58.000ZVITAL SIGNS INDICATOR Traffic Volumes at Regional Gateways (T6) FULL MEASURE NAME Daily vehicles along entry/exit points to the Bay Area LAST UPDATED April 2020 DESCRIPTION Traffic volumes at regional gateways refers to the number of vehicles crossing county boundaries on a typical day to enter or exit the nine-county San Francisco Bay Area. DATA SOURCE California Department of Transportation: Annual Traffic Volume Reports http://traffic-counts.dot.ca.gov CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Traffic counts reflect average annual daily traffic (AADT) counts at all state highway gateway points - entry/exit points to the nine-county San Francisco Bay Area. When the county line data was not available in the traffic volume reports, the closest intersection or interchange was used as a proxy for traffic volumes at the county line.