The water area of Hidden Valley Lake, CA was 0 in 2016.

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 Hidden Valley Lake, CA

  • API

    Citizen Statewide Lake Monitoring Assessment Program (CSLAP) Lakes

    data.ny.gov | Last Updated 2024-03-01T18:08:08.000Z

    The dataset represents the lakes participating in the Citizen Statewide Lake Monitoring Assessment Program (CSLAP). CSLAP is a volunteer lake monitoring and education program that is managed by DEC and New York State Federation of Lake Associations (NYSFOLA). The data collected through the program is used to identify water quality issues, detect seasonal and long term patterns, and inform volunteers and lake residents about water quality conditions in their lake. The program has delivered high quality data to many DEC programs for over 25 years.The dataset catalogs CSLAP lake information; including: lake name, lake depth, public accessibility, trophic status, watershed area, elevation, lake area, water quality classification, county, town, CSLAP status, years sampled, and last year sampled.

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    Public Fishing Rights Parking Areas

    data.ny.gov | Last Updated 2022-10-07T21:55:53.000Z

    The New York State Department of Environmental Conservation (DEC) maintains a network of Public Fishing Right parking areas along trout streams in New York. This dataset represents the locations and information about those parking areas. Links to PDF maps of the actual Public Fishing Rights along the streams are available as part of the data set.

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    Iowa Geographic Names

    mydata.iowa.gov | Last Updated 2024-09-20T22:00:21.000Z

    This dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names. The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.

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    Environmental Sensitivity Project (2015)

    data.edmonton.ca | Last Updated 2022-12-13T23:03:09.000Z

    Historically, the City of Edmonton has managed ‘natural areas’ within the North Saskatchewan River Valley and the Tablelands separately, guided by inventories such as the Ribbon of Green and Geowest (1993). Over the past decade, City policy has shifted to manage natural areas with consideration of their role within an ecological network. Today, a goal of the City is to protect, preserve and enhance a functioning ecological network throughout the city limits. This network should include lands in both the river valley and the Tablelands. To further this goal, a model was developed in 2015 for determining environmental sensitivity scores across the entirety of the city. This model guided the collection of several digital data layers with coverage across the entire study area (including several ecological assets, threats to assets, and development and cultural constraints). Data layers were then used to develop spatial outputs that summarized the distribution of these assets, threats and constraints. These base layers have been compiled into this dataset to help inform planning, development and conservation throughout Edmonton. Environmental sensitivity analysis incorporated recent mapping of the ecological network of native and non-native vegetation, streams, wetlands and other waterbodies as much as possible, with practical limitations. The City’s urban Primary Land and Vegetation Inventory (uPLVI) and remote sensing data used for this assessment were completed in 2015 and 2013 respectively, which is relatively recent, but not current. Similarly, infrastructure data (roads, subdivision development and stormwater facilities) provided varied in month of acquisition from 2015. Some discrepancy between mapped and actual features may result, due to loss and changes from ongoing development activities.

  • 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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    PUBLISH_PRMD_BASE_PLA_URBAN_SVC_AREA

    data.bayareametro.gov | Last Updated 2024-10-16T12:31:46.000Z

    Note: The Sonoma Valley Urban Service Area was revised by the Board of Supervisors as part of the Sonoma Developmental Center Specific Plan (File PLP22-0024) adopted by Ordinance 6400 and General Plan Resolution 22-0556 on December 16, 2022. The Sonoma Valley Urban Service Areas expanded into the SDC core campus portion of APN 054-090-001, and was removed from the SDC open space portion of APN 054-150-005.The Urban Service Areas (USA) dataset represents the designated limit to the urban development of unincorporated communities per Sonoma County's General Plan 2020 as adopted on September 23, 2008 by Resolution No. 08-0808. Currently, there are 21 unincorporated urban service communities within Sonoma County. The communities are limited to urban development through urban services which is the full range of public services and infrastructures including sewer, water, police and fire protection, roads, transit, etc. Per General Plan Land Use 2020 adopted on 09/23/2008 by the Board of Supervisors, USA's were updated to reflect changes in service areas, spheres of influence and city urban growth boundaries (Reso. No. 08-0808). To note, according to 2012 California Environmental Quality Act (CEQA) Guidelines Chapter 2.5 Definitions addresses "Urbanized Area" and defines "urban growth boundary" as a provision of a locally adopted general plan that allows urban uses one side of the boundary and prohibits urban uses on the other side.The 21 Urban Service Areas are as follows: AirportBodega BayCloverdaleCotatiForestvilleGeyservilleGratonGuernevilleHealdsburgLarkfieldMonte RioOccidentalPenngrovePetalumaRohnert ParkSanta RosaSea RanchSebastopolSonomaSonoma ValleyWindsor

  • API

    CA Water Resources Regional Offices

    data.bayareametro.gov | Last Updated 2024-07-17T18:57:17.000Z

    The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. It defines the areal extent of surface water drainage to a point except in coastal or lake front areas where there could be multiple outlets as stated by the "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" “Standard” (http://pubs.usgs.gov/tm/11/a3/). Watershed boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. This dataset represents the hydrologic unit boundaries to the 12-digit (6th level) for the entire United States. Some areas may also include additional subdivisions representing the 14- and 16-digit hydrologic unit (HU). At a minimum, the HUs are delineated at 1:24,000-scale in the conterminous United States, 1:25,000-scale in Hawaii, Pacific basin and the Caribbean, and 1:63,360-scale in Alaska, meeting the National Map Accuracy Standards (NMAS). Higher resolution boundaries are being developed where partners and data exist and will be incorporated back into the WBD. WBD data are delivered as a dataset of polygons and corresponding lines that define the boundary of the polygon. WBD polygon attributes include hydrologic unit codes (HUC), size (in the form of acres and square kilometers), name, downstream hydrologic unit code, type of watershed, non-contributing areas, and flow modifications. The HUC describes where the unit is in the country and the level of the unit. WBD line attributes contain the highest level of hydrologic unit for each boundary, line source information and flow modifications.

  • API

    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.

  • API

    RSBS SMO: Part 2 of 2, New York State Residential Statewide Baseline Study: Single and Multifamily Occupant Telephone or Web Survey

    data.ny.gov | Last Updated 2019-11-15T21:50:04.000Z

    How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. This is part 2 (contains: Clothes Washing and Drying; Water Heating; Home Lighting; Pool and Spa; Small Household Appliances; and Miscellaneous Equipment) of 2; part 1 (https://data.ny.gov/d/3m6x-h3qa) contains: Behavior and Demographics; Building Shell; Kitchen Appliances; and Heating and Cooling. The New York State Energy Research and Development Authority (NYSERDA), in collaboration with the New York State Department of Public Service (DPS), conducted a statewide residential baseline study (study) from 2011 to 2014 of the single-family and multifamily residential housing segments, including new construction, and a broad range of energy uses and efficiency measures. This dataset includes 2,982 single-family and 379 multifamily occupant survey completes for a total of 3,361 responses. The survey involved 2,285 Web, 1,041 telephone, and 35 mini-inspection surveys. The survey collected information on the following building characteristics: building shell, kitchen appliances, heating and cooling equipment, water heating equipment, clothes washing and drying equipment, lighting, pool and spa equipment, small household appliances, miscellaneous energy consuming equipment, as well as behaviors and characteristics of respondents.