20 datasets found
  1. a

    Parcel Map Index

    • hub.arcgis.com
    • gis-cupertino.opendata.arcgis.com
    • +1more
    Updated Oct 16, 2015
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    City of Cupertino (2015). Parcel Map Index [Dataset]. https://hub.arcgis.com/maps/Cupertino::parcel-map-index
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    Dataset updated
    Oct 16, 2015
    Dataset authored and provided by
    City of Cupertino
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Parcel Map Index is a Polygon FeatureClass showing approximate boundaries of Parcel Map recorded at Santa Clara County Clerk Recorders Office. Records are indexed by City assigned Parcel Map number. It is primarily used as a reference layer. The layer is updated as needed by the GIS Division. Parcel Map Index has the following fields:

    OBJECTID: Unique identifier automatically generated by Esri type: OID, length: 4, domain: none

    Parcel: The Assessor's Parcel Number type: String, length: 7, domain: none

    created_date: The date the database row was initially created type: Date, length: 8, domain: none

    last_edited_date: The date the database row was last updated type: Date, length: 8, domain: none

    Shape: Field that stores geographic coordinates associated with feature type: Geometry, length: 4, domain: none

    BookPage:

    type: String, length: 50, domain: none

    Shape.STArea():

    The area of the shape - in square feet type: Double, length: 0, domain: none

    Shape.STLength():

    The length of the shape - in feet type: Double, length: 0, domain: none

  2. K

    City of San Jose Parks

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 5, 2018
    + more versions
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    City of San Jose, California (2018). City of San Jose Parks [Dataset]. https://koordinates.com/layer/95883-city-of-san-jose-parks/
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    mapinfo tab, kml, shapefile, csv, pdf, geodatabase, mapinfo mif, dwg, geopackage / sqliteAvailable download formats
    Dataset updated
    Sep 5, 2018
    Dataset authored and provided by
    City of San Jose, California
    Area covered
    Description

    This layer was created as an update the existing San Jose Parks Layer (PRK.PARKS). The existing layer has been maintained by the City of San Jose Department of Public Works and had not been updated in some time. This layer is a draft as of (05.02.2014) and has not been fully reviewed to assure complete accuracy of boundaries. Nevertheless it is an improvement over the existing layer and has had park boundaries adjusted to reflect PRNS management authority to the curb and gutter. This layer is also primarily based upon satellite imagery and visible property lines with the Santa Clara County parcel layer used as a guide in certain circumstances where boundaries could not be identified. The PRK.PARKS layer on the other hand , appeared to be based upon the Santa Clara Parcel layer, which did not include sidewalk and curb areas of the parks. In addition many parcel maps features included sections of roadway or overlapped into neighboring properties when compared with the aerial. Park chains have yet to be reviewed and revised. It is our intent to adjust these features to show only secured or quasi-government lands in which development in unlikely to occur. In addition, park chain lands may be adjusted to reflect underpasses where trails and public access is permitted.

    © City of San Jose

  3. a

    Santa Clara County Map Grid

    • gis-cupertino.opendata.arcgis.com
    Updated Aug 18, 2016
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    City of Cupertino (2016). Santa Clara County Map Grid [Dataset]. https://gis-cupertino.opendata.arcgis.com/datasets/8e8b80e7706e4897a8909b65b795ba65
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    Dataset updated
    Aug 18, 2016
    Dataset authored and provided by
    City of Cupertino
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Santa Clara County Map Grid is a Polygon FeatureClass representing a map grid for Santa Clara County. It is primarily used as a reference layer. The layer is updated as needed by the GIS Division. Santa Clara County Map Grid has the following fields:

    OBJECTID_1: Unique identifier automatically generated by Esri type: OID, length: 4, domain: none

    Shape: Field that stores geographic coordinates associated with feature type: Geometry, length: 4, domain: none

    OBJECTID: Unique identifier automatically generated by Esri type: Integer, length: 4, domain: none

    GRID_NO: Field indicating the grid number type: String, length: 10, domain: none

    Label_MB:

    type: String, length: 4, domain: none

    Label11x17: Field containing the label for 11 x 17 formats type: String, length: 3, domain: none

    Label_Esize: Field containing the label for E file formats type: String, length: 3, domain: none

    GlobalID: Unique identifier automatically generated for features in enterprise database type: GlobalID, length: 38, domain: none

    SHAPE_Leng: The length of the shape - in feet type: Double, length: 8, domain: none

    IsCupertino: Field indicating whether or not the map grid section is within the City of Cupertino city limits type: String, length: 3, domain: shdBooleanYesNo domain values:['Yes', 'No']

    Shape_Area: The area of the shape - in square feet type: Double, length: 0, domain: none

    Shape_Length: The length of the shape - in feet type: Double, length: 0, domain: none

  4. c

    BOE TRA 2023 co43

    • gis.data.ca.gov
    • hub.arcgis.com
    Updated May 22, 2023
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    California Department of Tax and Fee Administration (2023). BOE TRA 2023 co43 [Dataset]. https://gis.data.ca.gov/datasets/CDTFA::santa-clara-2023-roll-year?layer=1
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    Dataset updated
    May 22, 2023
    Dataset authored and provided by
    California Department of Tax and Fee Administration
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This shapefile contains tax rate area (TRA) boundaries in Santa Clara County for the specified assessment roll year. Boundary alignment is based on the 2012 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

  5. a

    BOE TRA 2024 co43

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gis.data.ca.gov
    Updated Jun 3, 2024
    + more versions
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    California Department of Tax and Fee Administration (2024). BOE TRA 2024 co43 [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/CDTFA::boe-tra-2024-co43
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    Dataset updated
    Jun 3, 2024
    Dataset authored and provided by
    California Department of Tax and Fee Administration
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This shapefile contains tax rate area (TRA) boundaries in Santa Clara County for the specified assessment roll year. Boundary alignment is based on the 2012 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

  6. Santa Clara Public Health Profile Small Area/Neighborhood Index

    • data-sccphd.opendata.arcgis.com
    Updated Mar 14, 2018
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    Santa Clara County Public Health (2018). Santa Clara Public Health Profile Small Area/Neighborhood Index [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/santa-clara-public-health-profile-small-area-neighborhood-index/about
    Explore at:
    Dataset updated
    Mar 14, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Small area /neighborhood names in Santa Clara County. The areas shown on the map were calculated using Census 2010 tract boundaries and are combined into areas with a common place name. Input was provided by city and county planning departments. The boundaries shown are not considered definitive, but rather general in nature. Any naming will be partially correct, and partially incorrect. These boundaries were also required to follow the outlines of census tract boundaries and thus will not follow, in all instances, boundary lines which may be deemed more appropriate.

  7. T

    Buildings

    • data.bayareametro.gov
    Updated Mar 17, 2025
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    (2025). Buildings [Dataset]. https://data.bayareametro.gov/dataset/Buildings/cex7-xp4t
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    tsv, application/rdfxml, xml, csv, application/rssxml, application/geo+json, kmz, kmlAvailable download formats
    Dataset updated
    Mar 17, 2025
    Description

    This map data layer represents the building footprints for the City of Cupertino, California. The mapped geographic area includes 11.3 square miles of western Santa Clara County in California. The building footprints data layer was originally based on aerial photographs from 2011. Continual updates are made as needed. Most updates come from digitized plat/plan approvals or from completed City project plans. Mapping accuracy meets National Map Accuracy Standards for +/-2.5 US feet. Spatial coordinate system is California State Plane West, zone III Fipszone 0403 Adszone 3326, NAD83. Scale of true display is 1:1200 (100' scale).

  8. Population Density GIS

    • data-sccphd.opendata.arcgis.com
    • hub.arcgis.com
    Updated Aug 24, 2022
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    Santa Clara County Public Health (2022). Population Density GIS [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/population-density-gis
    Explore at:
    Dataset updated
    Aug 24, 2022
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Table contains total population and population density summarized at county, city, zip code, and census tract level. Population density is defined as number of people residing per square mile of area. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B01001; data accessed on April 11, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (String): Geography IDNAME (String): Name of geographyt_pop (Numeric): Total populationpop_density (Numeric): Area in square milesarea (Numeric): Population density

  9. Travel Model Super Districts

    • opendata.mtc.ca.gov
    • hub.arcgis.com
    Updated Mar 19, 2018
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    MTC/ABAG (2018). Travel Model Super Districts [Dataset]. https://opendata.mtc.ca.gov/datasets/travel-model-super-districts
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    Dataset updated
    Mar 19, 2018
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Descriptions of Metropolitan Transportation Commission's 34 Super DistrictsSuper District #1 - Greater Downtown San Francisco: This area, the northeastern quadrant of the city, is bounded by Van Ness Avenue on the west, 11th Street on the southwest, and Townsend Street on the south. This Super District includes the following neighborhoods and districts: Financial District, Union Square, Tenderloin, Civic Center, South of Market, South Park, Rincon Hill, Chinatown, Jackson Square, Telegraph Hill, North Beach, Nob Hill, Russian Hill, Polk Gulch and Fisherman's Wharf. Treasure Island and Yerba Buena Island are also part of Super District #1.Super District #2 - Richmond District: This area, the northwestern quadrant of the city, is bounded by Van Ness Avenue on the east, Market Street on the southeast, and 17th Street, Stanyan Street, and Lincoln Way on the south. Super District #2 includes the following neighborhoods and districts: the Presidio, the Western Addition District, the Marina, Cow Hollow, Pacific Heights, Cathedral Hill, Japantown, Hayes Valley, Duboce Triangle, the Haight-Ashbury, the Richmond District, Inner Richmond, Outer Richmond, Laurel Heights, Sea Cliff, and the Golden Gate Park.Super District #3 - Mission District: This area, the southeastern quadrant of the city, is bounded by Townsend Street, 11th Street, Market Street, 17th Street, Stanyan Street, and Lincoln Way on the northern boundary; 7th Avenue, Laguna Honda, Woodside Avenue, O'Shaughnessy Boulevard and other smaller streets (Juanita, Casita, El Verano, Ashton, Orizaba) on the western boundary; and by the San Mateo County line on the southern boundary. Super District #3 includes the following neighborhoods and districts: China Basin, Potrero Hill, Inner Mission, Outer Mission, Twin Peaks, Parnassus Heights, Dolores Heights, Castro, Eureka Valley, Noe Valley, Bernal Heights, Glen Park, Ingleside, Ocean View, the Excelsior, Crocker-Amazon, Visitacion Valley, Portola, Bayview, and Hunters Point.Super District #4 - Sunset District: This area, the southwestern quadrant of the city, is bounded by Lincoln Way (Golden Gate Park) on the north; 7th Avenue, Laguna Honda, Woodside Avenue, O'Shaughnessy Boulevard and other smaller streets (Juanita, Casita, El Verano, Ashton, Orizaba) on the eastern boundary; and by the San Mateo County line on the southern boundary. Super District #4 includes the following neighborhoods and districts: Inner Sunset, the Sunset District, Sunset Heights, Parkside, Lake Merced District, Park-Merced, Ingleside Heights, West Portal and St. Francis Wood.Super District #5 - Daly City/San Bruno: This northern San Mateo County Super District includes the communities of Daly City, Colma, Brisbane, South San Francisco, Pacifica, San Bruno, Millbrae, and the north part of Burlingame. The boundary between Super District #5 and Super District #6 is Broadway, Carmelita Avenue, El Camino Real, Easton Drive, the Hillsborough / Burlingame city limits, Interstate 280, Skyline Boulevard, the Pacifica city limits, and the Montara Mountain ridgeline extending to Devil's Slide on the coast.Super District #6 - San Mateo/Burlingame: The central San Mateo County Super District includes the communities of Hillsborough, San Mateo, Foster City, Belmont, the southern part of Burlingame, and the coastside communities of Montara, Moss Beach, El Granada, and Half Moon Bay. The southern boundary of Super District #6 is the Foster City city limits, the Belmont/San Carlos city limits, Interstate 280, Kings Mountain, Lobitos Creek extending to Martins Beach on the coast.Super District #7 - Redwood City/Menlo Park: The southern San Mateo County Super District includes the communities of San Carlos, Redwood Shores, Redwood City, Atherton, Menlo Park, East Palo Alto, Woodside, Portola Valley, and the coastside communities of San Gregorio and Pescadero.Super District #8 - Palo Alto/Los Altos: This Santa Clara County Super District includes the communities of Palo Alto, Los Altos, Los Altos Hills, and the western part of Mountain View. Boundaries include the San Mateo County line, US-101 on the north, and Cal-85 (Stevens Creek Freeway) and Stevens Creek on the east.Super District #9 - Sunnyvale/Mountain View: This is the "Silicon Valley" Super District and includes the communities of Mountain View (eastern part and shoreline), Sunnyvale, Santa Clara (northern part), Alviso, and San Jose (northern part). Also included in this Super District is the "Golden Triangle" district. Super District #9 is bounded by US-101, Cal-85, Stevens Creek on the western boundary; Homestead Road on the southern boundary; Pierce Street, Civic Center Drive and the SP tracks in Santa Clara City; and Interstate 880 as the eastern boundary.Super District #10 - Cupertino/Saratoga: This Super District is located in south central Santa Clara County and includes the communities of Cupertino, Saratoga, Santa Clara City (southern part), Campbell (western part), San Jose (western part), Monte Sereno, Los Gatos and Redwood Estates. This area is bounded by Stevens Creek and the Santa Cruz Mountains on the west, Homestead Road on the north, Interstate 880/California Route 17 on the east; Union Avenue, Camden Avenue and Hicks Road (San Jose) also on the eastern boundary; and the Santa Clara/Santa Cruz county line on the south.Super District #11 - Central San Jose: This central Santa Clara County Super District is comprised of San Jose (central area), Santa Clara City (downtown area), and Campbell (east of Cal-17). The general boundaries of Super District #11 are Interstate 880/California Route 17 on the west; US-101 on the east; and the Capitol Expressway, Hillsdale Avenue, Camden Avenue, and Union Avenue on the south boundary.Super District #12 - Milpitas/East San Jose: This eastern Santa Clara County Super District includes the City of Milpitas, and the East San Jose communities of Berryessa, Alum Rock, and Evergreen. Boundaries include Interstate 880 and US-101 freeways on the west; San Jose City limits (Evergreen) on the south; and the mountains on the east.Super District #13 - South San Jose: This south-central Santa Clara County Super District includes the southern part of San Jose including the Almaden and Santa Teresa neighborhoods. Super District #13 is surrounded by Super District #10 on the west; Super District #11 on the north; Super District #12 on the northeast; and Super District #14 on the south at Metcalf Road (Coyote).Super District #14 - Gilroy/Morgan Hill: This area of Santa Clara County is also known as "South County" and includes the communities of Gilroy, Morgan Hill, San Martin and the Coyote Valley. Also included in this Super District are Loma Prieta (western boundary of the Super District) and Mount Hamilton in the northeastern, rural portion of Santa Clara County. This area is bounded by Santa Cruz and San Benito Counties on the south, and Merced and Stanislaus Counties on the eastern border.Super District #15 - Livermore/Pleasanton: This is the eastern Alameda County Super District including the Livermore and Amador Valley communities of Livermore, Pleasanton, Dublin, San Ramon Village, and Sunol. This Super District includes all of eastern Alameda County east of Pleasanton Ridge and Dublin Canyon.Super District #16 - Fremont/Union City: The southern Alameda County Super District includes the communities of Fremont, Newark and Union City. The boundaries for this Super District are the Hayward/Union City city limits on the north side; the hills to the immediate east; the Santa Clara/Alameda County line on the south; and the San Francisco Bay on the west.Super District #17 - Hayward/San Leandro: This southern Alameda County Super District includes the communities of Hayward, San Lorenzo, San Leandro, Castro Valley, Cherryland, and Ashland. The northern border is the San Leandro/Oakland city limits.Super District #18 - Oakland/Alameda: This northern Alameda County Super District includes the island city of Alameda, Oakland, and Piedmont. The Oakland neighborhoods of North Oakland and Rockridge are in the adjacent Super District #19. The border between Super Districts #18 and #19 are the Oakland/Emeryville city limits; 52nd and 51st Streets; Broadway; and Old Tunnel Road.Super District #19 - Berkeley/Albany: This northern Alameda County Super District includes all of Emeryville, Berkeley, and Albany, and the Oakland neighborhoods in North Oakland and Rockridge. The Super District is surrounded by the Alameda/Contra Costa County lines; the San Francisco Bay; and the Oakland Super District.Super District #20 - Richmond/El Cerrito: This is the western Contra Costa Super District. It includes the communities of Richmond, El Cerrito, Kensington, Richmond Heights, San Pablo, El Sobrante, Pinole, Hercules, Rodeo, Crockett, and Port Costa. The eastern boundary to Super District #20 is defined as the Carquinez Scenic Drive (east of Port Costa); McEwen Road; California Route 4; Alhambra Valley Road; Briones Road through the Regional Park; Bear Creek Road; and Wildcat Canyon Road to the Alameda/Contra Costa County line.Super District #21 - Concord/Martinez: This is one of three central Contra Costa County Super Districts. Super District #21 includes the communities of Concord, Martinez, Pleasant Hill, Clayton, and Pacheco. This area is bounded by Suisun Bay on the north; Willow Pass and Marsh Creek on the east; Mt Diablo on the southeast; and Cowell Road, Treat Boulevard, Oak Grove Road, Minert Road, Bancroft Road, Oak Park Boulevard, Putnam Boulevard, Geary Road, and Pleasant Hill Road on the south; and Briones Park, Alhambra Valley Road and Cal-4 on the west.Super District #22 - Walnut Creek: This central Contra Costa County Super District includes the communities of Walnut Creek, Lafayette, Moraga and Orinda. The latter three communities are more popularly known as Lamorinda. The border with Super District #23 generally follows the southern city limits of Walnut Creek.Super

  10. S

    Neighborhood Business Districts

    • data.sanjoseca.gov
    • gisdata-csj.opendata.arcgis.com
    Updated Jan 27, 2023
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    Enterprise GIS (2023). Neighborhood Business Districts [Dataset]. https://data.sanjoseca.gov/dataset/neighborhood-business-districts
    Explore at:
    csv, kml, html, arcgis geoservices rest api, geojson, zipAvailable download formats
    Dataset updated
    Jan 27, 2023
    Dataset provided by
    City of San José
    Authors
    Enterprise GIS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    These are commercial areas along both sides of a street, which function in their neighborhoods or communities as central business districts, providing community focus and identity through the delivery of goods and services. In addition, Neighborhood Business Districts may include adjacent non-commercial land uses. Neighborhood Business Districts (NBDs) contain a variety of commercial and noncommercial uses which contribute to neighborhood identity by serving as a focus for neighborhood activity. This designation facilitates the implementation of a NBD Program by identifying target areas. The NBD Program seeks to preserve, enhance, and revitalize San José’s neighborhood-serving commercial areas through the coordination of public and private improvements, such as streetscape beautification, facade upgrading, business organization activities, business development, and promotional events. Consistent with its Implementation and Community Design Policies, the City will schedule, coordinate, and design public improvements in Neighborhood Business Districts so that allocated funding is consistent with the City’s growth strategies.

    The NBD designation functions as an “overlay” designation which is applied to predominantly commercial land use designations. It is typically applied to two types of commercial areas. The first is older commercial areas where connected buildings create a predominant pattern of a continuous street façade with no, or very small setbacks from the sidewalk. Examples of this include Lincoln Avenue between Coe and Minnesota Avenues, Jackson Street between 4th and 6th Streets, and the segment of Alum Rock Avenue between King Road and Interstate 680. The second commercial area where the NBD overlay is applied typically contains a series of one or more of the following development types: parking lot strips (buildings set back with parking in front), neighborhood centers (one or two anchors plus smaller stores in one complex), or traditional, older commercial areas as described in the first NBD typology.

    NBDs generally surround Main Street designations on the Transportation Network Diagram. The exceptions are The Alameda and East Santa Clara Street, which are noted as Grand Boulevards. NBDs can extend beyond the parcels immediately adjacent to a Main Street or Grand Boulevard, and they often overlap with Urban Village Boundary Area designations. Within an NBD overlay, residential and commercial uses, together with related parking facilities, are seen to be complementary uses, although commercial uses oriented to occupants of vehicles, such as drive-through service windows, are discouraged along major thoroughfares within NBD areas. In areas with an NBD overlay designation, any new development or redevelopment must conform to the underlying land use designation and applicable Urban Village Plans, Land Use Policies, and Community Design Policies. Such development must also conform to design guidelines adopted by the City.

    Data has never been updated.

  11. Bike Superhighway 2022

    • data.vta.org
    • data-mountainview.opendata.arcgis.com
    Updated Oct 6, 2022
    + more versions
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    Santa Clara Valley Transportation Authority (2022). Bike Superhighway 2022 [Dataset]. https://data.vta.org/maps/8c33cfa9dbc442728edde518e3067371
    Explore at:
    Dataset updated
    Oct 6, 2022
    Dataset authored and provided by
    Santa Clara Valley Transportation Authorityhttp://www.vta.org/
    Area covered
    Description

    The Bicycle Superhighway priority network as identified in the Bicycle Superhighway Implementation Plan, adopted by the VTA Board in 2021. Bicycle superhighways are high quality, uninterrupted, long-distance bikeways separated from motor vehicles that traverse across the county. The bicycle superhighway network will allow people to travel quickly from city to city by bicycle in much the same way the County Expressway System allows people to travel quickly across the county by car. In practice, the bicycle superhighway network will consist of a network of high-quality, low-stress, on-street bikeways and trails. When properly designed, bicyclists using them typically experience less delay due to fewer at-grade crossings with the street network or due to signal priority at intersections. Many proposed segments require more planning and funding.

  12. a

    Data from: Municipal Boundary

    • data-mountainview.opendata.arcgis.com
    • hub.arcgis.com
    Updated Oct 17, 2015
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    City of Mountain View (2015). Municipal Boundary [Dataset]. https://data-mountainview.opendata.arcgis.com/maps/municipal-boundary
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    Dataset updated
    Oct 17, 2015
    Dataset authored and provided by
    City of Mountain View
    Area covered
    Description

    This dataset represents the contents of the municipal boundaries of Santa Clara county as provided by the County of Santa Clara GIS program

  13. a

    Police Reporting Districts

    • hub.arcgis.com
    • sunnyvale-geohub-cityofsunnyvale.hub.arcgis.com
    Updated Apr 7, 2021
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    Vestra_CityofSunnyvale (2021). Police Reporting Districts [Dataset]. https://hub.arcgis.com/maps/11b2aec9d76044dc9428f40a22cc566f_0/about
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    Dataset updated
    Apr 7, 2021
    Dataset authored and provided by
    Vestra_CityofSunnyvale
    Area covered
    Description

    All city boundaries and unincorporated areas in Santa Clara County

  14. a

    Demographic Statistics - Small Area/Neighborhood

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 21, 2018
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    Santa Clara County Public Health (2018). Demographic Statistics - Small Area/Neighborhood [Dataset]. https://hub.arcgis.com/maps/eb57d42a2dd74372a45940b77cffc607_0/about
    Explore at:
    Dataset updated
    Feb 21, 2018
    Dataset authored and provided by
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Neighborhood; Population Size; African American; Asian/Pacific Islander; Latino; White; Foreign-born; Speaks a language other than English at home; Single parent households; Households with children; Average household size; 0-5 years; 6-11 years; 12-17 years; 18-24 years; 25-34 years; 35-44 years; 45-54 years; 55-64 years; Ages 65 and older; Ages 17 and younger. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

  15. a

    People Below 200% FPL GIS

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Aug 24, 2022
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    Santa Clara County Public Health (2022). People Below 200% FPL GIS [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/ee1ae7791d4648e9b80b31f2917bf0dd
    Explore at:
    Dataset updated
    Aug 24, 2022
    Dataset authored and provided by
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Table contains count and percentage of county residents living below the 200% of Federal Poverty Level (FPL). Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table C17002; data accessed on April 11, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographypop (Numeric): Population for whom poverty status was assessedfpl200 (Numeric): Number of people living below 200% of Federal Poverty Levelpct_200 (Numeric): Percent of people living below 200% of Federal Poverty Level

  16. a

    Building Footprints

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Oct 16, 2015
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    City of Cupertino (2015). Building Footprints [Dataset]. https://hub.arcgis.com/maps/Cupertino::building-footprints
    Explore at:
    Dataset updated
    Oct 16, 2015
    Dataset authored and provided by
    City of Cupertino
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Building Footprint is a Polygon FeatureClass representing the building footprints for the City of Cupertino, California. The mapped geographic area includes 11.3 square miles of western Santa Clara County in California. The building footprints data layer was originally based on aerial photographs from 2011. Continual updates are made as needed. Most updates come from digitized plat/plan approvals or from completed City project plans. Mapping accuracy meets National Map Accuracy Standards for +/-2.5 US feet. Spatial coordinate system is California State Plane West, zone III Fipszone 0403 Adszone 3326, NAD83. Scale of true display is 1:1200 (100' scale). Building Footprints has the following fields: OBJECTID: Unique identifier automatically generated by Esri type: OID, length: 4, domain: none

    LEVEL_DESC: A general description of what type of structure the polygon represents type: String, length: 18, domain: none

    BLDG_HIGH: The height of the highest point on the polygon - feet above sea level type: String, length: 50, domain: none

    BLDG_LOW: The height of the lowest point on the polygon - feet above see level type: String, length: 50, domain: none

    FloorNumbe: The number of floors the building has type: Integer, length: 4, domain: none

    AssetID: Cupertino maintained GIS primary key type: String, length: 50, domain: none

    Year_Built: The year the building was built type: Date, length: 8, domain: none

    Bldg_Age: The age of the building type: Single, length: 4, domain: none

    LegacyID: Old identifiers used to track asset migration type: Integer, length: 4, domain: none

    Shape: Field that stores geographic coordinates associated with feature type: Geometry, length: 4, domain: none

    GlobalID: Unique identifier automatically generated for features in enterprise database type: GlobalID, length: 38, domain: noneShape.STArea():The area of the building footprinttype: double, length: none, domain: none Shape.STLength(): The length of the perimeter of the building footprinttype: double, length: none, domain: none BLDG_HEIGHT: The height of the building, calculated by subtracting the highest and lowest points type: double, length: none, domain: none

    last_edited_date: The date the database row was last updated type: Date, length: 8, domain: none

    created_date: The date the database row was initially created type: Date, length: 8, domain: none

  17. a

    California Statewide Parcel Boundaries

    • hub.arcgis.com
    • data.lacounty.gov
    • +1more
    Updated Jul 8, 2020
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    County of Los Angeles (2020). California Statewide Parcel Boundaries [Dataset]. https://hub.arcgis.com/documents/baaf8251bfb94d3984fb58cb5fd93258
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    Dataset updated
    Jul 8, 2020
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    California
    Description

    This dataset includes one file for each of the 51 counties that were collected, as well as a CA_Merged file with the parcels merged into a single file.Note – this data does not include attributes beyond the parcel ID number (PARNO) – that will be provided when available, most likely by the state of California.DownloadA 1.6 GB zipped file geodatabase is available for download - click here.DescriptionA geodatabase with parcel boundaries for 51 (out of 58) counties in the State of California. The original target was to collect data for the close of the 2013 fiscal year. As the collection progressed, it became clear that holding to that time standard was not practical. Out of expediency, the date requirement was relaxed, and the currently available dataset was collected for a majority of the counties. Most of these were distributed with minimal metadata.The table “ParcelInfo” includes the data that the data came into our possession, and our best estimate of the last time the parcel dataset was updated by the original source. Data sets listed as “Downloaded from” were downloaded from a publicly accessible web or FTP site from the county. Other data sets were provided directly to us by the county, though many of them may also be available for direct download. Â These data have been reprojected to California Albers NAD84, but have not been checked for topology, or aligned to county boundaries in any way. Tulare County’s dataset arrived with an undefined projection and was identified as being California State Plane NAD83 (US Feet) and was assigned by ICE as that projection prior to reprojection. Kings County’s dataset was delivered as individual shapefiles for each of the 50 assessor’s books maintained at the county. These were merged to a single feature class prior to importing to the database.The attribute tables were standardized and truncated to include only a PARNO (APN). The format of these fields has been left identical to the original dataset. The Data Interoperablity Extension ETL tool used in this process is included in the zip file. Where provided by the original data sources, metadata for the original data has been maintained. Please note that the attribute table structure changes were made at ICE, UC Davis, not at the original data sources.Parcel Source InformationCountyDateCollecDateCurrenNotesAlameda4/8/20142/13/2014Download from Alamenda CountyAlpine4/22/20141/26/2012Alpine County PlanningAmador5/21/20145/14/2014Amador County Transportation CommissionButte2/24/20141/6/2014Butte County Association of GovernmentsCalaveras5/13/2014Download from Calaveras County, exact date unknown, labelled 2013Contra Costa4/4/20144/4/2014Contra Costa Assessor’s OfficeDel Norte5/13/20145/8/2014Download from Del Norte CountyEl Dorado4/4/20144/3/2014El Dorado County AssessorFresno4/4/20144/4/2014Fresno County AssessorGlenn4/4/201410/13/2013Glenn County Public WorksHumboldt6/3/20144/25/2014Humbodt County AssessorImperial8/4/20147/18/2014Imperial County AssessorKern3/26/20143/16/2014Kern County AssessorKings4/21/20144/14/2014Kings CountyLake7/15/20147/19/2013Lake CountyLassen7/24/20147/24/2014Lassen CountyLos Angeles10/22/201410/9/2014Los Angeles CountyMadera7/28/2014Madera County, Date Current unclear likely 7/2014Marin5/13/20145/1/2014Marin County AssessorMendocino4/21/20143/27/2014Mendocino CountyMerced7/15/20141/16/2014Merced CountyMono4/7/20144/7/2014Mono CountyMonterey5/13/201410/31/2013Download from Monterey CountyNapa4/22/20144/22/2014Napa CountyNevada10/29/201410/26/2014Download from Nevada CountyOrange3/18/20143/18/2014Download from Orange CountyPlacer7/2/20147/2/2014Placer CountyRiverside3/17/20141/6/2014Download from Riverside CountySacramento4/2/20143/12/2014Sacramento CountySan Benito5/12/20144/30/2014San Benito CountySan Bernardino2/12/20142/12/2014Download from San Bernardino CountySan Diego4/18/20144/18/2014San Diego CountySan Francisco5/23/20145/23/2014Download from San Francisco CountySan Joaquin10/13/20147/1/2013San Joaquin County Fiscal year close dataSan Mateo2/12/20142/12/2014San Mateo CountySanta Barbara4/22/20149/17/2013Santa Barbara CountySanta Clara9/5/20143/24/2014Santa Clara County, Required a PRA requestSanta Cruz2/13/201411/13/2014Download from Santa Cruz CountyShasta4/23/20141/6/2014Download from Shasta CountySierra7/15/20141/20/2014Sierra CountySolano4/24/2014Download from Solano Couty, Boundaries appear to be from 2013Sonoma5/19/20144/3/2014Download from Sonoma CountyStanislaus4/23/20141/22/2014Download from Stanislaus CountySutter11/5/201410/14/2014Download from Sutter CountyTehama1/16/201512/9/2014Tehama CountyTrinity12/8/20141/20/2010Download from Trinity County, Note age of data 2010Tulare7/1/20146/24/2014Tulare CountyTuolumne5/13/201410/9/2013Download from Tuolumne CountyVentura11/4/20146/18/2014Download from Ventura CountyYolo11/4/20149/10/2014Download from Yolo CountyYuba11/12/201412/17/2013Download from Yuba County

  18. a

    Utah Address System Quadrants

    • hub.arcgis.com
    • opendata.gis.utah.gov
    • +2more
    Updated Aug 10, 2016
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    Utah Automated Geographic Reference Center (AGRC) (2016). Utah Address System Quadrants [Dataset]. https://hub.arcgis.com/maps/utah::utah-address-system-quadrants
    Explore at:
    Dataset updated
    Aug 10, 2016
    Dataset authored and provided by
    Utah Automated Geographic Reference Center (AGRC)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    Last update: April 4, 2023Added the Mammoth address system in Juab county. Additional minor edits to account for annexations in Utah (Springville, Lehi) and Box Elder (Willard, Garland) counties, April 2023.Added several address grids in Beaver county (Elk Meadows, Ponderosa, Greenville, Adamsville, Sulphurdale). Made major updates to grids in Utah, Cache, Tooele, and Box Elder Counties. Renamed 'NSL' to 'North Salt Lake' and 'East Carbon City' to 'East Carbon', December 2022. Minor adjustment to quadrants in Bluff.Added Rocky Ridge address grid in northern Juab county, August 2022.Updates were made near Elsinore/Central Valley/Monroe corners due to recent Elsinore annexation and inputs from Sevier County, September 2021.Improvements were made to Brigham City, Millville, Logan, and Providence, February 2016.Improvements were made to the Heber, Hyde Park, Logan, and Woodland address system boundaries; updated the American Fork, Fielding, Payson, and Saratoga Springs address system boundaries to reflect recent annexations, January 2016Improvements were made to the Hyde Park and Logan address system boundary, November 2015Improvements were made to the Hyrum and Logan address system boundary, November 2015Updated the American Fork address system boundary to reflect recent annexations, October 2015Improvements were made to the Brigham City, Fishlake, Fremont, Garland, Loa, Lyman, Mantua, Tremonton, and Willard address system boundaries; updated the Lehi and Santa Clara address system boundaries to reflect recent annexations, August 2015Improvements were made to the Price and Wellington address system boundaries; updated the Lehi and Provo address system boundaries to reflect recent annexations, July 2015Improvements were made to the Layton and HAFB address system boundaries; updated the Provo and Spanish Fork address system boundaries to reflect recent annexations, June 2015Updated address system boundaries to reflect annexations in Lehi, Lewiston, and Snowville, May 2015Improvements were made to the Orderville address system boundary to match the municipal boundary, February 2015Updated address system boundaries to match annexations in American Fork, Farmington, Elk Ridge, Grantsville, Lehi, Mendon, Mount Pleasant, Payson, Provo, Spanish Fork, and Washington, January 2015 Improvements were made to the Elmo and Cleveland address system boundaries, December 2014Improvements were made to the Wellington address system boundaries, July 2014Improvements were made to the NSL (North Salt Lake) and Bountiful address system boundaries, June 2014.Changed address system name East Carbon-Sunnyside to East Carbon City, May 2014Updated address system boundaries to match annexations in northern Utah County; misc improvements in Davis County; adjusted Laketown/Garden City boundary, April 2014Merged East Carbon and Sunnyside to create the East Carbon-Sunnyside address system, February 2014.Improvements were made to the Iron County address system quadrant boundaries and topological errors were corrected statewide, January 2014. Improvements were made to Garfield County and Washington County address system quadrant boundaries, August 2013.More information can be found on the UGRC data page for this layer:https://gis.utah.gov/data/location/address-data/

  19. a

    Health Status Statistics - Zip Code

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 21, 2018
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    Santa Clara County Public Health (2018). Health Status Statistics - Zip Code [Dataset]. https://hub.arcgis.com/maps/sccphd::health-status-statistics-zip-code
    Explore at:
    Dataset updated
    Feb 21, 2018
    Dataset authored and provided by
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Zip Code, Life expectancy; Cancer deaths per 100,000 people; Heart disease deaths per 100,000 people; Alzheimer’s disease deaths per 100,000 people; Stroke deaths per 100,000 people; Chronic lower respiratory disease deaths per 100,000 people; Unintentional injury deaths per 100,000 people; Diabetes deaths per 100,000 people; Influenza and pneumonia deaths per 100,000 people; Hypertension deaths per 100,000 people. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

  20. a

    Soil Type

    • gisdata-csj.opendata.arcgis.com
    • data.sanjoseca.gov
    Updated Aug 27, 2020
    + more versions
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    City of San José (2020). Soil Type [Dataset]. https://gisdata-csj.opendata.arcgis.com/datasets/CSJ::soil-type/about
    Explore at:
    Dataset updated
    Aug 27, 2020
    Dataset authored and provided by
    City of San José
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Boundaries of various soil types within San Jose, CA.Data is published on Mondays on a weekly basis.

  21. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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City of Cupertino (2015). Parcel Map Index [Dataset]. https://hub.arcgis.com/maps/Cupertino::parcel-map-index

Parcel Map Index

Explore at:
Dataset updated
Oct 16, 2015
Dataset authored and provided by
City of Cupertino
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Area covered
Description

Parcel Map Index is a Polygon FeatureClass showing approximate boundaries of Parcel Map recorded at Santa Clara County Clerk Recorders Office. Records are indexed by City assigned Parcel Map number. It is primarily used as a reference layer. The layer is updated as needed by the GIS Division. Parcel Map Index has the following fields:

OBJECTID: Unique identifier automatically generated by Esri type: OID, length: 4, domain: none

Parcel: The Assessor's Parcel Number type: String, length: 7, domain: none

created_date: The date the database row was initially created type: Date, length: 8, domain: none

last_edited_date: The date the database row was last updated type: Date, length: 8, domain: none

Shape: Field that stores geographic coordinates associated with feature type: Geometry, length: 4, domain: none

BookPage:

type: String, length: 50, domain: none

Shape.STArea():

The area of the shape - in square feet type: Double, length: 0, domain: none

Shape.STLength():

The length of the shape - in feet type: Double, length: 0, domain: none

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