The land area of Day Valley, CA was 19 in 2018. The land area of Lincoln Village, CA was 1 in 2018.

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 - Notes:

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Geographic and Area Datasets Involving Day Valley, CA or Lincoln Village, CA

  • 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.

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    Vital Signs: Fatalities From Crashes – by metro

    data.bayareametro.gov | Last Updated 2018-07-06T18:04:13.000Z

    VITAL SIGNS INDICATOR Injuries From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED October 2017 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the National Highway Safety Administration's Fatalities Analysis Reporting System. 2016 data comes from the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and California Department of Finance and vehicle miles traveled (VMT) data from the Federal Highway Administration. For more regarding reporting procedures and injury classification see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

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    Vital Signs: Fatalities From Crashes – Bay Area

    data.bayareametro.gov | Last Updated 2018-07-06T18:04:09.000Z

    VITAL SIGNS INDICATOR Injuries From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED October 2017 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the National Highway Safety Administration's Fatalities Analysis Reporting System. 2016 data comes from the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and California Department of Finance and vehicle miles traveled (VMT) data from the Federal Highway Administration. For more regarding reporting procedures and injury classification see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

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    Vital Signs: Fatalities From Crashes – by crash

    data.bayareametro.gov | Last Updated 2018-07-06T18:04:12.000Z

    VITAL SIGNS INDICATOR Injuries From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED October 2017 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the National Highway Safety Administration's Fatalities Analysis Reporting System. 2016 data comes from the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and California Department of Finance and vehicle miles traveled (VMT) data from the Federal Highway Administration. For more regarding reporting procedures and injury classification see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

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    Vital Signs: Fatalities From Crashes – by county

    data.bayareametro.gov | Last Updated 2018-07-06T18:04:07.000Z

    VITAL SIGNS INDICATOR Injuries From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED October 2017 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the National Highway Safety Administration's Fatalities Analysis Reporting System. 2016 data comes from the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and California Department of Finance and vehicle miles traveled (VMT) data from the Federal Highway Administration. For more regarding reporting procedures and injury classification see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

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    Wildfire - Fire Risk and Fire Responsibility Areas (HESS)

    data.bayareametro.gov | Last Updated 2023-06-09T19:12:13.000Z

    Wildfire - Fire Risk and Fire Responsibility Areas (CAL FIRE) for development of the Parcel Inventory dataset for the Housing Element Site Selection (HESS) Pre-Screening Tool. ** This data set represents Moderate, High, and Very High Fire Hazard Severity Zones in State Responsibility Areas (SRA) and Very High Fire Hazard Severity Zones in Local Responsibility Areas (LRA) for the San Francisco Bay Region and some of its surrounding counties. The data was assembled by the Metropolitan Transportation Commission from multiple shapefiles provided by the California Department of Forestry and Fire Protection. The SRA data was extracted from a statewide shapefile and the LRA data is a combination of county shapefiles. All source data was downloaded from the Office of the State Fire Marshal's Fire Hazard Severity Zones Maps page (https://osfm.fire.ca.gov/divisions/community-wildfire-preparedness-and-mitigation/wildland-hazards-building-codes/fire-hazard-severity-zones-maps/). ** State Responsibility Areas PRC 4201 - 4204 and Govt. Code 51175-89 direct CAL FIRE to map areas of significant fire hazards based on fuels, terrain, weather, and other relevant factors. These zones, referred to as Fire Hazard Severity Zones (FHSZ), define the application of various mitigation strategies to reduce risk associated with wildland fires. CAL FIRE is remapping FHSZ for SRA and Very High Fire Hazard Severity Zones (VHFHSZ) recommendations in LRA to provide updated map zones, based on new data, science, and technology. Local Responsibility Areas Government Code 51175-89 directs the CAL FIRE to identify areas of very high fire hazard severity zones within LRA. Mapping of the areas, referred to as VHFHSZ, is based on data and models of, potential fuels over a 30-50 year time horizon and their associated expected fire behavior, and expected burn probabilities to quantify the likelihood and nature of vegetation fire exposure (including firebrands) to buildings. Details on the project and specific modeling methodology can be found at https://frap.cdf.ca.gov/projects/hazard/methods.html. Local Responsibility Area VHFHSZ maps were initially developed in the mid-1990s and are now being updated based on improved science, mapping techniques, and data. Local government had 120 days to designate, by ordinance, very high fire hazard severity zones within their jurisdiction after receiving the CAL FIRE recommendations. Local governments were able to add additional VHFHSZs. There was no requirement for local government to report their final action to CAL FIRE when the recommended zones are adopted. Consequently, users are directed to the appropriate local entity (county, city, fire department, or Fire Protection District) to determine the status of the local fire hazard severity zone ordinance. In late 2005, to be effective in 2008, the California Building Commission adopted California Building Code Chapter 7A requiring new buildings in VHFHSZs to use ignition resistant construction methods and materials. These new codes include provisions to improve the ignition resistance of buildings, especially from firebrands. The updated very high fire hazard severity zones will be used by building officials for new building permits in LRA. The updated zones will also be used to identify property whose owners must comply with natural hazards disclosure requirements at time of property sale and 100 foot defensible space clearance. It is likely that the fire hazard severity zones will be used for updates to the safety element of general plans.

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    Vital Signs: Fatalities From Crashes – By Case (2022) DRAFT

    data.bayareametro.gov | Last Updated 2022-12-11T07:45:10.000Z

    VITAL SIGNS INDICATOR Fatalities From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED May 2022 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). For more regarding reporting procedures and injury classification, see the California Highway Patrol Manual (https://one.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

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    Baseline Study of Food for Peace Title II Development Food Assistance Program in Niger-- Household Sanitation and Maternal Health

    datahub.usaid.gov | Last Updated 2024-07-12T09:55:20.000Z

    This dataset captures data about the mothers in the households surveyed as part of the Baseline Study of Food for Peace Title II Development Food Assistance Program in the Maradi and Zinder regions in Niger as well as the water and sanitation resources available to the household. It has 200 columns and 7,337 rows. In fiscal year 2012, USAID's Office of Food for Peace (FFP) awarded funding to private voluntary organizations (PVOs) to design and implement a multi-year Title II development food assistance program in Niger. The main purpose of the Title II program is to improve long-term food security of chronically food insecure population in the target regions. FFP contracted a firm, ICF International to conduct a baseline study in targeted areas of the country prior to the start of the new program. The purpose of the study was to assess the current status of key indicators, have a better understanding of prevailing conditions and perceptions of the population in the implementation areas, and serve as a point of comparison for future final evaluations. Results would also be used to further refine program targeting and, where possible, to understand the relationship between variables to inform program design. The study was conducted in 2013, while FFP expects to conduct final evaluations as close as possible to the end of the program five years later.

  • API

    Baseline Study of Food for Peace Title II Development Food Assistance Program in Karamoja, Uganda--Maternal Health and Household Sanitation

    datahub.usaid.gov | Last Updated 2024-07-12T09:17:17.000Z

    This dataset captures data about the mothers in the households surveyed as part of the Baseline Study of Food for Peace Title II Development Food Assistance Program in Karamoja, Uganda as well as the water and sanitation resources available to the household. This dataset contains data from Modules F and J of the questionnaire and has 295 columns and 4,766 rows. In fiscal year 2012, USAID's Office of Food for Peace (FFP) awarded funding to private voluntary organizations (PVOs) to design and implement a multi-year Title II development food assistance program in Uganda. The main purpose of the Title II program is to improve long-term food security of chronically food insecure population in the target regions. FFP contracted a firm, ICF International to conduct a baseline study in targeted areas of the country prior to the start of the new program. The purpose of the study was to assess the current status of key indicators, have a better understanding of prevailing conditions and perceptions of the population in the implementation areas, and serve as a point of comparison for future final evaluations. Results would also be used to further refine program targeting and, where possible, to understand the relationship between variables to inform program design. The study was conducted in 2013, while FFP expects to conduct final evaluations as close as possible to the end of the program five years later. The data asset is comprised of six datasets: 1) a description of all members of the households surveyed, 2) data on maternal health and sanitation practices, 3) data about the children in the household, 4) data describing the agricultural practices of the household, 5) data describing the food consumption of the household (broken into 4 smaller spreadsheets), and 6) and a description of the weights that should be applied during the analysis of the other datasets.

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    Current Descriptive Data of Municipal Wastewater Treatment Plants

    data.ny.gov | Last Updated 2019-06-10T18:04:47.000Z

    Data containing municipal wastewater treatment plant design other features, with data current through the most recent survey.