38 datasets found
  1. Vegetation - San Mateo County [ds3021]

    • gis.data.ca.gov
    • data.cnra.ca.gov
    • +5more
    Updated Mar 11, 2024
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    California Department of Fish and Wildlife (2024). Vegetation - San Mateo County [ds3021] [Dataset]. https://gis.data.ca.gov/datasets/048fa54a97fe404db2255e5fdb935a28
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    Dataset updated
    Mar 11, 2024
    Dataset authored and provided by
    California Department of Fish and Wildlifehttps://wildlife.ca.gov/
    License

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

    Area covered
    Description

    In 2018, the Golden Gate National Parks Conservancy (Parks Conservancy) (https://parksconservancy.org), non-profit support partner to the National Park Service (NPS) Golden Gate National Recreation Area (GGNRA), initiated a fine scale vegetation mapping project in Marin County. The GGNRA includes lands in San Francisco and San Mateo counties, and NPS expressed interest in pursuing fine scale vegetation mapping for those lands as well. The Parks Conservancy facilitated multiple meetings with potential project stakeholders and was able to build a consortium of funders to map all of San Mateo County (and NPS lands in San Francisco). The consortium included the San Francisco Public Utilities Commission (SFPUC), Midpeninsula Regional Open Space District (MROSD), Peninsula Open Space Trust (POST), San Mateo City/County Association of Governments, and various County of San Mateo departments including Parks, Agricultural Weights and Measures, Public Works/Flood Control District, Office of Sustainability, and Planning and Building. Over a 3-year period, the project, collectively referred to as the “San Mateo Fine Scale Veg Map”, has produced numerous environmental GIS products including 1-foot contours, orthophotography, and other land cover maps. A 106-class fine-scale vegetation map was completed in April 2022 that details vegetation communities and agricultural land cover types, including forests, grasslands, riparian vegetation, wetlands, and croplands. The environmental data products from the San Mateo Fine Scale Veg Map are foundational and can be used by organizations and government departments for a wide range of purposes, including planning, conservation, and to track changes over time to San Mateo County’s habitats and natural resources.Development of the San Mateo fine-scale vegetation map was managed by the Golden Gate National Parks Conservancy and staffed by personnel from Tukman Geospatial (https://tukmangeospatial.com/), Aerial Information Systems (AIS; http://www.aisgis.com/), and Kass Green and Associates. The fine-scale vegetation map effort included field surveys by a team of trained botanists including Neal Kramer, Brett Hall, Lucy Ferneyhough, Brittany Burnett, Patrick Furtado, and Rosie Frederick. Data from these surveys, combined with older surveys from previous efforts, were analyzed by the California Native Plant Society (CNPS) Vegetation Program (https://www.cnps.org/vegetation), with support from the California Department of Fish and Wildlife Vegetation Classification and Mapping Program (VegCAMP; https://wildlife.ca.gov/Data/VegCAMP) and ecologists with NatureServe (https://www.natureserve.org/) to develop a San Mateo County-specific vegetation classification. For more information on the field sampling and vegetation classification work San Mateo County Fine Scale Vegetation Map Final Report refer to the final report (https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=212663) issued by CNPS and corresponding floristic descriptions (https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=212666 and https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=212667).Existing lidar data, collected in 2017 by San Mateo County was used to support the project. The lidar point cloud, and many of its derivatives, were used extensively during the process of developing the fine-scale vegetation and habitat map. The lidar data was used in conjunction with optical data. Optical data used throughout the project included 6-inch resolution airborne 4-band imagery collected in the summer of 2018, as well as various dates of National Agriculture Imagery Program (NAIP) imagery. Key data sets used in the lifeform and the enhanced lifeform mapping process include high resolution aerial imagery from 2018, the lidar-derived Canopy Height Model (CHM), and several other lidar-derived raster and vector datasets. In addition, a number of forest structure lidar derivatives are used in the machine learning portion of the enhanced lifeform workflow.In 2020, an enhanced lifeform map was produced which serves as the foundation for the much more floristically detailed fine-scale vegetation and habitat map. The lifeform map was developed using expert systems rulesets in Trimble Ecognition®, followed by manual editing.In 2020, Tukman Geospatial staff and partners conducted countywide reconnaissance field work to support fine-scale mapping. Field-collected data were used to train automated machine learning algorithms, which produced a fully automated countywide fine-scale vegetation and habitat map. Throughout 2021, AIS manually edited the fine-scale maps, and Tukman Geospatial and AIS went to the field for validation trips to inform and improve the manual editing process. In early January of 2022, draft maps were distributed and reviewed by San Mateo County’s community of land managers and by the funders of the project. Input from these groups was used to further refine the map. The countywide fine-scale vegetation map and related data products were made public in April 2022. In total, 106 vegetation classes were mapped. During the classification development phase, minimum mapping units (MMUs) were established for the vegetation mapping project. An MMU is the smallest area to be mapped on the ground. For this project, the mapping team chose to map different features at different MMUs. The MMU is 1/4 acre for agricultural, woody riparian, and wetland herbaceous classes; 1/2 acre for woody upland, upland herbaceous, and bare land classes; 1/5 acre for developed feature types; and 400 square feet for water.Accuracy assessment plot data were collected in 2021 and 2022. Accuracy assessment results were compiled and analyzed in the April of 2022. Overall accuracy of the lifeform map is 98 percent. Overall accuracy of the fine-scale vegetation map is 83.5 percent, with an overall ‘fuzzy’ accuracy of 90.8 percent.

  2. w

    San Mateo County Aerial Imagery Service 2017

    • data.wu.ac.at
    csv, json, xml
    Updated Nov 28, 2017
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    GIS Team, County of San Mateo Information Services Department (2017). San Mateo County Aerial Imagery Service 2017 [Dataset]. https://data.wu.ac.at/schema/performance_smcgov_org/ZWNyai1ydWp0
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    xml, json, csvAvailable download formats
    Dataset updated
    Nov 28, 2017
    Dataset provided by
    GIS Team, County of San Mateo Information Services Department
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    San Mateo County
    Description

    Aerial imagery map service of San Mateo County. Acquired in 2017. For use as a basemap in online maps.

    Spatial Reference: 102643 (2227) Pixel Size X: 0.5 Pixel Size Y: 0.5

    More information about the service itself can be found here: http://gis.co.sanmateo.ca.us/arcgis/rest/services/COMMON/SanMateoCounty_Imagery2017/ImageServer

  3. w

    County Shaded Relief Service 2006

    • data.wu.ac.at
    • data.smcgov.org
    csv, json, xml
    Updated Nov 28, 2017
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    GIS Team, County of San Mateo Information Services Department (2017). County Shaded Relief Service 2006 [Dataset]. https://data.wu.ac.at/schema/performance_smcgov_org/anVjNi1tejk5
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    xml, json, csvAvailable download formats
    Dataset updated
    Nov 28, 2017
    Dataset provided by
    GIS Team, County of San Mateo Information Services Department
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Shaded relief map service of San Mateo County. Derived from aerial imagery acquired in 2006. For use as a basemap in online maps and to show elevation change using shading.

    Spatial Reference: 102643 (2227) Pixel Size X: 5.0 Pixel Size Y: 5.0 Band Count: 3

    More information about the service itself can be found here: http://gis.co.sanmateo.ca.us/arcgis/rest/services/COMMON/SanMateoCounty_ShadedRelief2006/ImageServer

  4. a

    Data from: Scenic Corridors

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated May 18, 2016
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    San Mateo County (2016). Scenic Corridors [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/smcmaps::gis-data?layer=12
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    Dataset updated
    May 18, 2016
    Dataset authored and provided by
    San Mateo County
    License

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

    Area covered
    Description

    Location of scenic corridors around highways in San Mateo County. Scenic highway corridors are designated by cities, counties, and CalTrans. More information about the State's Scenic Corridor program can be found here: http://www.dot.ca.gov/hq/LandArch/16_livability/scenic_highways/faq.htm

  5. s

    Active Parcels with Assessor Parcel Numbers: San Mateo County, California,...

    • searchworks.stanford.edu
    zip
    Updated Jul 28, 2018
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    (2018). Active Parcels with Assessor Parcel Numbers: San Mateo County, California, 2015 [Dataset]. https://searchworks.stanford.edu/view/gd575cq2724
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    zipAvailable download formats
    Dataset updated
    Jul 28, 2018
    Area covered
    San Mateo County
    Description

    This coverage can be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

  6. w

    San Mateo County Digital Elevation Model Service 2017

    • data.wu.ac.at
    csv, json, xml
    Updated Nov 29, 2017
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    GIS Team, County of San Mateo Information Services Department (2017). San Mateo County Digital Elevation Model Service 2017 [Dataset]. https://data.wu.ac.at/schema/performance_smcgov_org/dmJ0cy1nYmJx
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    csv, xml, jsonAvailable download formats
    Dataset updated
    Nov 29, 2017
    Dataset provided by
    GIS Team, County of San Mateo Information Services Department
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    San Mateo County
    Description

    Digital elevation model (DEM) map service of San Mateo County. Includes elevation derived from aerial imagery acquired in 2016. For use as a basemap in online maps.

    Spatial Reference: 102643 (2227)

    More information about the service itself can be found here: http://gis.co.sanmateo.ca.us/arcgis/rest/services/COMMON/SanMateoCounty_DEM2017/ImageServer

  7. s

    Grid Boundaries (800 m): San Mateo County, California, 1999

    • searchworks.stanford.edu
    zip
    Updated May 8, 2024
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    (2024). Grid Boundaries (800 m): San Mateo County, California, 1999 [Dataset]. https://searchworks.stanford.edu/view/gd405kd7369
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    zipAvailable download formats
    Dataset updated
    May 8, 2024
    Area covered
    San Mateo County, California
    Description

    This polygon shapefile depicts 800 meter grid boundaries for the County of San Mateo. This layer is part of a collection of GIS data for San Mateo County, California.

  8. s

    County Boundary: San Mateo County, California, 2008

    • searchworks.stanford.edu
    zip
    Updated Jul 28, 2024
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    (2024). County Boundary: San Mateo County, California, 2008 [Dataset]. https://searchworks.stanford.edu/view/dq636dn9692
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    zipAvailable download formats
    Dataset updated
    Jul 28, 2024
    Area covered
    San Mateo County, California
    Description

    This polygon shapefile depicts the county boundary for San Mateo County in California. This layer is part of a collection of GIS data for San Mateo County, California.

  9. s

    City Boundaries: San Mateo County, California, 2015

    • searchworks.stanford.edu
    zip
    Updated Nov 7, 2019
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    (2019). City Boundaries: San Mateo County, California, 2015 [Dataset]. https://searchworks.stanford.edu/view/vg219yc9446
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    zipAvailable download formats
    Dataset updated
    Nov 7, 2019
    Area covered
    San Mateo County
    Description

    This coverage can be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

  10. s

    Open Space Areas: San Mateo County, California, 2015

    • searchworks.stanford.edu
    zip
    Updated Nov 19, 2014
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    (2014). Open Space Areas: San Mateo County, California, 2015 [Dataset]. https://searchworks.stanford.edu/view/sj663qc6996
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    zipAvailable download formats
    Dataset updated
    Nov 19, 2014
    Area covered
    San Mateo County
    Description

    This polygon shapefile depicts all open space areas within the County of San Mateo, California. This layer is part of a collection of GIS data for San Mateo County, California.

  11. a

    BOE TRA 2025 co41

    • cdtfa.hub.arcgis.com
    • gis.data.ca.gov
    • +2more
    Updated Jun 9, 2025
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    California Department of Tax and Fee Administration (2025). BOE TRA 2025 co41 [Dataset]. https://cdtfa.hub.arcgis.com/datasets/777b447221b54571ba871cac0bdc95e5
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    Dataset updated
    Jun 9, 2025
    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 San Mateo County for the specified assessment roll year. Boundary alignment is based on the 2021 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

  12. San Francisco Bay Region Spheres of Influence

    • opendata.mtc.ca.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Aug 23, 2019
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    MTC/ABAG (2019). San Francisco Bay Region Spheres of Influence [Dataset]. https://opendata.mtc.ca.gov/datasets/e9accd91e02f47bd83edea4781eeb187
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    Dataset updated
    Aug 23, 2019
    Dataset provided by
    Metropolitan Transportation Commission
    Authors
    MTC/ABAG
    License

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

    Area covered
    Description

    The California Association Local Agency Formation Commissions defines a sphere of influence (SOI) as "a planning boundary outside of an agency’s legal boundary (such as the city limit line) that designates the agency’s probable future boundary and service area." This feature set represents the SOIs of the incorporated jurisdictions for the San Francisco Bay Region. The Metropolitan Transportation Commission (MTC) updated the feature set in late 2019 as part of the jurisdiction review process for the BASIS data gathering project. Changes were made to the growth boundaries of the following jurisdictions based on BASIS feedback and associated work: Antioch, Brentwood, Campbell, Daly City, Dublin, Fremont, Hayward, Los Gatos, Monte Sereno, Newark, Oakland, Oakley, Pacifica, Petaluma, Pittsburg, Pleasanton, San Bruno, San Francisco (added to reflect other jurisdictions whose SOI is the same as their jurisdiction boundary), San Jose, San Leandro, Santa Clara, Saratoga, and Sunnyvale. Notes: With the exception of San Mateo and Solano Counties, counties included jurisdiction (city/town) areas as part of their SOI boundary data. San Mateo County and Solano County only provided polygons representing the SOI areas outside the jurisdiction areas. To create a consistent, regional feature set, the Metropolitan Transportation Commission (MTC) added the jurisdiction areas to the original, SOI-only features and dissolved the features by name.Because of differences in base data used by the counties and the MTC, edits were made to the San Mateo County and Solano County SOI features that should have been adjacent to their jurisdiction boundary so the dissolve function would create a minimum number of features. Original sphere of influence boundary acquisitions:Alameda County - CityLimits_SOI.shp received as e-mail attachment from Alameda County Community Development Agency on 30 August 2019 Contra Costa County - BND_LAFCO_Cities_SOI.zip downloaded from https://gis.cccounty.us/Downloads/Planning/ on 15 August 2019Marin County - 'Sphere of Influence - City' feature service data downloaded from Marin GeoHub on 15 August 2019Napa County - city_soi.zip downloaded from their GIS Data Catalog on 15 August 2019 City and County of San Francisco - does not have a sphere of influence San Mateo County - 'Sphere of Influence' feature service data downloaded from San Mateo County GIS open data on 15 August 2019 Santa Clara County - 'City Spheres of Influence' feature service data downloaded from Santa Clara County Planning Office GIS Data on 15 August 2019 Solano County - SphereOfInfluence feature service data downloaded from Solano GeoHub on 15 August 2019 Sonoma County - 'SoCo PRMD GIS Spheres Influence.zip' downloaded from County of Sonoma on 15 August 2019

  13. K

    San Mateo County, CA Streets

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 12, 2018
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    San Mateo County, California (2018). San Mateo County, CA Streets [Dataset]. https://koordinates.com/layer/97052-san-mateo-county-ca-streets/
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    kml, geodatabase, mapinfo mif, shapefile, geopackage / sqlite, csv, pdf, dwg, mapinfo tabAvailable download formats
    Dataset updated
    Sep 12, 2018
    Dataset authored and provided by
    San Mateo County, California
    Area covered
    Description

    This layer is a component of County Basemap NAD83.

  14. d

    California State Waters Map Series--Offshore of San Gregorio Web Services

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Apr 13, 2017
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    Guy R. Cochrane; Peter Dartnell; H. Gary Greene; Janet T. Watt; Nadine E. Golden; Charles A. Endris; Eleyne L. Phillips; Stephen R. Hartwell; Samuel Y. Johnson; Rikk G. Kvitek; Mercedes D. Erdey; Carrie .K. Bretz; Michael W. Mansion; Ray W. Sliter; Stephanie L. Ross; Brian E. Dieter; John L. Chin (2017). California State Waters Map Series--Offshore of San Gregorio Web Services [Dataset]. https://search.dataone.org/view/01910ab9-2107-4be1-a6db-96d5e5b7b8e8
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    Dataset updated
    Apr 13, 2017
    Dataset provided by
    USGS Science Data Catalog
    Authors
    Guy R. Cochrane; Peter Dartnell; H. Gary Greene; Janet T. Watt; Nadine E. Golden; Charles A. Endris; Eleyne L. Phillips; Stephen R. Hartwell; Samuel Y. Johnson; Rikk G. Kvitek; Mercedes D. Erdey; Carrie .K. Bretz; Michael W. Mansion; Ray W. Sliter; Stephanie L. Ross; Brian E. Dieter; John L. Chin
    Time period covered
    Jan 1, 2006 - Jan 1, 2015
    Area covered
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands†from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of San Gregorio map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and p... Visit https://dataone.org/datasets/01910ab9-2107-4be1-a6db-96d5e5b7b8e8 for complete metadata about this dataset.

  15. s

    Active Planning Zones: San Mateo County, California, 2014

    • searchworks.stanford.edu
    zip
    Updated Jun 12, 2021
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    (2021). Active Planning Zones: San Mateo County, California, 2014 [Dataset]. https://searchworks.stanford.edu/view/wf602dz2179
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    zipAvailable download formats
    Dataset updated
    Jun 12, 2021
    Area covered
    San Mateo County, California
    Description

    This coverage can be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

  16. s

    General Plan Land Use Areas: San Mateo County, California, 2015

    • searchworks.stanford.edu
    zip
    Updated Sep 18, 2019
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    (2019). General Plan Land Use Areas: San Mateo County, California, 2015 [Dataset]. https://searchworks.stanford.edu/view/nv364ks8979
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    zipAvailable download formats
    Dataset updated
    Sep 18, 2019
    Area covered
    San Mateo County, California
    Description

    This coverage can be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

  17. s

    Open Space Ward Boundaries: San Mateo County, California, 2015

    • searchworks.stanford.edu
    zip
    Updated Jan 27, 2021
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    (2021). Open Space Ward Boundaries: San Mateo County, California, 2015 [Dataset]. https://searchworks.stanford.edu/view/zd538mg8762
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    zipAvailable download formats
    Dataset updated
    Jan 27, 2021
    Area covered
    San Mateo County
    Description

    This coverage can be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

  18. O

    California School Campus Database

    • data.smcgov.org
    • data.wu.ac.at
    csv, xlsx, xml
    Updated Dec 12, 2016
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    The first release of CSCD was developed by the Stanford Prevention Research Center and GreenInfo Network, with funding from the Tobacco-Related Disease Research Program grant #22RT-0142, PI: Lisa Henriksen, PhD. (2016). California School Campus Database [Dataset]. https://data.smcgov.org/Education/California-School-Campus-Database/sa7d-zpha/about
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    csv, xml, xlsxAvailable download formats
    Dataset updated
    Dec 12, 2016
    Dataset authored and provided by
    The first release of CSCD was developed by the Stanford Prevention Research Center and GreenInfo Network, with funding from the Tobacco-Related Disease Research Program grant #22RT-0142, PI: Lisa Henriksen, PhD.
    Area covered
    California
    Description

    CCSD is a GIS data set that contains detailed outlines of the lands used by public schools for educational purposes. The campus boundaries of schools with kindergarten through 12th grade instruction are each accurately mapped at the assessor parcel level. CCSD is the first statewide database of this information and is available for use without restriction.

  19. A

    i15 LandUse SanMateo2012

    • data.amerigeoss.org
    Updated Feb 16, 2022
    + more versions
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    United States (2022). i15 LandUse SanMateo2012 [Dataset]. https://data.amerigeoss.org/es/dataset/i15-landuse-sanmateo2012-498b8
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    csv, geojson, html, zip, arcgis geoservices rest api, kmlAvailable download formats
    Dataset updated
    Feb 16, 2022
    Dataset provided by
    United States
    Description

    This map is designated as Final.

    Land-Use Data Quality Control

    Every published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.

    Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.

    Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.

    The 2012 San Mateo County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use boundaries were digitized and land use data was gathered by staff of DWR’s North Central Region using extensive field visits and aerial photography. TLand use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters, under the leadership of Jean Woods, and North Central Region, under the supervision of Kim Rosmaier. This data was developed to monitor land use for the primary purpose of quantifying water use within this study area and determining changes in water use associated with land use changes over time. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of San Mateo County conducted by the California Department of Water Resources, North Central Regional Office staff. The field work for this survey was conducted during June 2012 by staff visiting each field and noting what was grown. Land use field boundaries were digitized using ArcGIS 10.0 with 2010 National Agriculture Imagery Program (NAIP) one-meter imagery as the base. Field boundaries were reviewed and updated using 2012 NAIP imagery when it became available. Field boundaries were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. Images and land use boundaries were loaded onto laptop computers that were used as the field data collection tools. GPS units connected to the laptops were used to confirm surveyor's location with respect to the fields. Staff took these laptops into the field and virtually all the areas were visited to positively identify the land use. Land use codes were digitized in the field on laptop computers using ESRI ArcMAP software, version 10.0. Before final processing, standard quality control procedures were performed jointly by staff at DWR’s North Central Region, and at DSIWM headquarters under the leadership of Jean Woods. Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the orthorectified NAIP imagery, is approximately 6 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

  20. d

    California State Waters Map Series--Offshore of Half Moon Bay Web Services

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    • data.usgs.gov
    • +4more
    Updated Jun 1, 2017
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    Guy R. Cochrane; Peter Dartnell; H. Gary Greene; Samuel Y. Johnson; Nadine E. Golden; Stephen R. Hartwell; Bryan E. Dieter; Michael W. Mansion; Ray W. Sliter; Stephanie L. Ross; Janet T. Watt; Charles A. Endris; Rikk G. Kvitek; Brian D. Edwards; Eleyne L. Phillips; Mercedes D. Erdey; Carrie K. Bretz; John L. Chin; Carrie K. Bretz (2017). California State Waters Map Series--Offshore of Half Moon Bay Web Services [Dataset]. https://search.dataone.org/view/30b5b382-4e43-4723-b06b-51faa842c4c1
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    Dataset updated
    Jun 1, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Guy R. Cochrane; Peter Dartnell; H. Gary Greene; Samuel Y. Johnson; Nadine E. Golden; Stephen R. Hartwell; Bryan E. Dieter; Michael W. Mansion; Ray W. Sliter; Stephanie L. Ross; Janet T. Watt; Charles A. Endris; Rikk G. Kvitek; Brian D. Edwards; Eleyne L. Phillips; Mercedes D. Erdey; Carrie K. Bretz; John L. Chin; Carrie K. Bretz
    Time period covered
    Jan 1, 2006 - Jan 1, 2015
    Area covered
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands†from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Half Moon Bay map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and ... Visit https://dataone.org/datasets/30b5b382-4e43-4723-b06b-51faa842c4c1 for complete metadata about this dataset.

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California Department of Fish and Wildlife (2024). Vegetation - San Mateo County [ds3021] [Dataset]. https://gis.data.ca.gov/datasets/048fa54a97fe404db2255e5fdb935a28
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Vegetation - San Mateo County [ds3021]

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Dataset updated
Mar 11, 2024
Dataset authored and provided by
California Department of Fish and Wildlifehttps://wildlife.ca.gov/
License

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

Area covered
Description

In 2018, the Golden Gate National Parks Conservancy (Parks Conservancy) (https://parksconservancy.org), non-profit support partner to the National Park Service (NPS) Golden Gate National Recreation Area (GGNRA), initiated a fine scale vegetation mapping project in Marin County. The GGNRA includes lands in San Francisco and San Mateo counties, and NPS expressed interest in pursuing fine scale vegetation mapping for those lands as well. The Parks Conservancy facilitated multiple meetings with potential project stakeholders and was able to build a consortium of funders to map all of San Mateo County (and NPS lands in San Francisco). The consortium included the San Francisco Public Utilities Commission (SFPUC), Midpeninsula Regional Open Space District (MROSD), Peninsula Open Space Trust (POST), San Mateo City/County Association of Governments, and various County of San Mateo departments including Parks, Agricultural Weights and Measures, Public Works/Flood Control District, Office of Sustainability, and Planning and Building. Over a 3-year period, the project, collectively referred to as the “San Mateo Fine Scale Veg Map”, has produced numerous environmental GIS products including 1-foot contours, orthophotography, and other land cover maps. A 106-class fine-scale vegetation map was completed in April 2022 that details vegetation communities and agricultural land cover types, including forests, grasslands, riparian vegetation, wetlands, and croplands. The environmental data products from the San Mateo Fine Scale Veg Map are foundational and can be used by organizations and government departments for a wide range of purposes, including planning, conservation, and to track changes over time to San Mateo County’s habitats and natural resources.Development of the San Mateo fine-scale vegetation map was managed by the Golden Gate National Parks Conservancy and staffed by personnel from Tukman Geospatial (https://tukmangeospatial.com/), Aerial Information Systems (AIS; http://www.aisgis.com/), and Kass Green and Associates. The fine-scale vegetation map effort included field surveys by a team of trained botanists including Neal Kramer, Brett Hall, Lucy Ferneyhough, Brittany Burnett, Patrick Furtado, and Rosie Frederick. Data from these surveys, combined with older surveys from previous efforts, were analyzed by the California Native Plant Society (CNPS) Vegetation Program (https://www.cnps.org/vegetation), with support from the California Department of Fish and Wildlife Vegetation Classification and Mapping Program (VegCAMP; https://wildlife.ca.gov/Data/VegCAMP) and ecologists with NatureServe (https://www.natureserve.org/) to develop a San Mateo County-specific vegetation classification. For more information on the field sampling and vegetation classification work San Mateo County Fine Scale Vegetation Map Final Report refer to the final report (https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=212663) issued by CNPS and corresponding floristic descriptions (https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=212666 and https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=212667).Existing lidar data, collected in 2017 by San Mateo County was used to support the project. The lidar point cloud, and many of its derivatives, were used extensively during the process of developing the fine-scale vegetation and habitat map. The lidar data was used in conjunction with optical data. Optical data used throughout the project included 6-inch resolution airborne 4-band imagery collected in the summer of 2018, as well as various dates of National Agriculture Imagery Program (NAIP) imagery. Key data sets used in the lifeform and the enhanced lifeform mapping process include high resolution aerial imagery from 2018, the lidar-derived Canopy Height Model (CHM), and several other lidar-derived raster and vector datasets. In addition, a number of forest structure lidar derivatives are used in the machine learning portion of the enhanced lifeform workflow.In 2020, an enhanced lifeform map was produced which serves as the foundation for the much more floristically detailed fine-scale vegetation and habitat map. The lifeform map was developed using expert systems rulesets in Trimble Ecognition®, followed by manual editing.In 2020, Tukman Geospatial staff and partners conducted countywide reconnaissance field work to support fine-scale mapping. Field-collected data were used to train automated machine learning algorithms, which produced a fully automated countywide fine-scale vegetation and habitat map. Throughout 2021, AIS manually edited the fine-scale maps, and Tukman Geospatial and AIS went to the field for validation trips to inform and improve the manual editing process. In early January of 2022, draft maps were distributed and reviewed by San Mateo County’s community of land managers and by the funders of the project. Input from these groups was used to further refine the map. The countywide fine-scale vegetation map and related data products were made public in April 2022. In total, 106 vegetation classes were mapped. During the classification development phase, minimum mapping units (MMUs) were established for the vegetation mapping project. An MMU is the smallest area to be mapped on the ground. For this project, the mapping team chose to map different features at different MMUs. The MMU is 1/4 acre for agricultural, woody riparian, and wetland herbaceous classes; 1/2 acre for woody upland, upland herbaceous, and bare land classes; 1/5 acre for developed feature types; and 400 square feet for water.Accuracy assessment plot data were collected in 2021 and 2022. Accuracy assessment results were compiled and analyzed in the April of 2022. Overall accuracy of the lifeform map is 98 percent. Overall accuracy of the fine-scale vegetation map is 83.5 percent, with an overall ‘fuzzy’ accuracy of 90.8 percent.

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