Under contract to the Santa Cruz Mountains Stewardship Network with support from the Golden Gate National Parks Conservancy, and staffed by personnel from Tukman Geospatial, Aerial Information Systems (AIS), and Kass Green and Associates, Tukman Geospatial and Aerial Information Systems created a fine-scale vegetation map of portions of Santa Cruz and Santa Clara Counties. CDFW’s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. The mapping study area, consists of approximately 1,133,106.8 acres, of Santa Clara and Santa Cruz counties. Work was performed on the project between 2020 and 2023. The Santa Cruz and Santa Clara fine-scale vegetation map was designed for a broad audience for use at many floristic and spatial scales and is useful to managers interested in specific information about vegetation composition and forest health.CNPS under separate contract and in collaboration with CDFW VegCAMP developed the floristic vegetation classification used for the project. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS).The vegetation map was produced with countywide vegetation survey data and combined with surveys from CNPS. Trimble® Ecognition® followed by manual image interpretation that was used to map lifeforms. Fine-scale segmentation was conducted using Trimble Ecognition® and relies on summer 2020 4-band NAIP, the 2020 lidar-derived canopy height model, and a suite of spectral indices derived from the NAIP. They utilized a type of algorithmic data modeling known as machine learning to automate the classification of fine-scale segments into one of Santa Cruz and Santa Clara Counties 121 fine-scale map classes. The minimum mapping unit (MMU) is set by feature type. For agricultural classes, the MMU is 1/4 acre, for woody upland classes is 1/2 acre, woody riparian is 1/4 acre, upland herbaceous is 1/2 acre, wetland herbaceous is 1/4 acre. Bare land is 1/2 acre, impervious features is 1000 square feet, while developed is 1/5 acre and water is 400 square feet.Field reconnaissance and accuracy assessment enhanced map quality. There was a total of 121 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map, map at the Alliance and Group levels, is 92 percent. More information can be found in the project report, which is bundled with the vegetation map published for BIOs here: https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199

Geospatial data about Santa Cruz County, California Watersheds. Export to CAD, GIS, PDF, CSV and access via API.

Geospatial data about Santa Cruz County, California Culverts. Export to CAD, GIS, PDF, CSV and access via API.

Geospatial data about Santa Cruz County, California Zoning. Export to CAD, GIS, PDF, CSV and access via API.

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. 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.

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. 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.

THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

© 2017, County of Santa Clara, SCVWD, USGS, SFEI, OSM

Boundaries of incorporated Cities within Santa Cruz County, California. In some cases, these include properties owned by cities but outside of contiguous city boundaries.City Limits are administered by Santa Cruz County Local Agency Formation Commission (LAFCO).

Landcover of Santa Clara County which has been derived from the The National Land Cover Database 2011 (NLCD 2011). National Land Cover Database 2011 (NLCD 2011) is the most recent national land cover product created by the Multi-Resolution Land Characteristics (MRLC) Consortium. NLCD 2011 provides - for the first time - the capability to assess wall-to-wall, spatially explicit, national land cover changes and trends across the United States from 2001 to 2011. As with two previous NLCD land cover products NLCD 2011 keeps the same 16-class land cover classification scheme that has been applied consistently across the United States at a spatial resolution of 30 meters. NLCD 2011 is based primarily on a decision-tree classification of circa 2011 Landsat satellite data.

THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

© County of Santa Clara, SCVWD, USGS, SFEI, 2017

http://geo-nsdi.er.usgs.gov/metadata/open-file/98-792/metadata.faq.html#getacopy.4 A 1:62,500-scale black-and-white map identifying some 2,000 landslides of various types in Santa Cruz County, California.

THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

© Santa Clara County Combined data (2012), All rights reserved

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. 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.

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

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 Pigeon Point to South Monterey Bay Region 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 vid... Visit https://dataone.org/datasets/624b6171-c94b-4c32-ad93-58a0165230e7 for complete metadata about this dataset.

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. 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.

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 Aptos 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 photogra... Visit https://dataone.org/datasets/23730b0d-26c5-4213-bb30-bd37e9dc7760 for complete metadata about this dataset.

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. 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.

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 2014 Santa Clara 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 were gathered by staff of DWR’s North Central Region using extensive field visits and aerial photography. Land 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 aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. 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 Santa Clara County conducted by the California Department of Water Resources, North Central Regional Office staff. Land use field boundaries were digitized with ArcGIS 10.3 using 2012 U.S.D.A National Agriculture Imagery Program (NAIP) one-meter imagery as the base. Agricultural fields were delineated by following actual field boundaries instead of using the centerlines of roads to represent the field borders. Field boundaries were reviewed and updated using 2014 Landsat 8 imagery and 2014 U.S.D.A National Agriculture Imagery Program (NAIP) one-meter imagery after it became available in late 2014. The county boundary is based on the CalFire updated State and County boundary layer dated 2009. Field boundaries were not drawn to represent legal parcel (ownership) boundaries, and are not meant to be used as parcel boundaries. The field work for this survey was conducted from June 16, 2014 through July 24, 2014. Images, land use boundaries and ESRI ArcMap software were loaded onto laptop computers that were used as the field data collection tools. Staff took these laptops into the field and virtually all agricultural fields were visited to identify the land use. Global positioning System (GPS) units connected to the laptops were used to confirm the surveyor's location with respect to the fields. Land use codes were digitized in the field using dropdown selections from defined domains. Upon completion of the survey, a Python script was used to convert the data table into the standard land use format. ArcGIS geoprocessing tools and topology rules were used to locate errors for quality control. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed. Rural residential land use was delineated by drawing polygons to surround houses and other buildings along with some of the surrounding land. These footprint areas do not represent the entire footprint of urban land. Sources of irrigation water were not identified for most areas. The exception is the area of the Corde Valle Golf Course near San Martin and a few nearby fields where recycled water is used as a water source in addition to groundwater. 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.

A GIS polygon shapefile outlining the boundaries of the native input datasets used to construct a seamless, 2-meter resolution digital elevation model (DEM) was constructed for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the North-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 m elevation contour.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.