Dataset Summary:This 3-foot resolution Digital Terrain Model (DTM) depicts topography, while removing all above-ground objects on the earth’s surface, like trees and buildings. The DTM represents the state of the landscape when countywide LiDAR data was collected in 2018 and 2020. Figure 1 shows the vintages of LiDAR contained in this raster. Quality level 1 LiDAR (QL1, red areas in figure 1) was collected in 2018. Quality level 2 LiDAR (QL2) was collected in summer, 2020.Figure 1. Recent LiDAR collections, by Quality Level (QL) in Santa Cruz County Methods:This LiDAR derivative provides information about the bare surface of the earth. The 3-foot resolution raster was produced from 2018 Quality Level 2 and 2020 Quality Level 1 LiDAR point cloud data (already ground classified) using Lastools. The processing steps were as followsCreate Tiles (lastile)Create DTM from ground classified points (las2dem)N Note that this DTM is neither hydro-flattened nor hydro-enforced.Uses and Limitations:The DTM provides a raster depiction of the ground returns for each 3x3 foot raster cell across Santa Cruz County. The layer is useful for hydrologic and terrain-focused analysis. The DTM will be most accurate in open terrain and less accurate in areas of very dense vegetation.Related Datasets:This dataset is part of a suite of LiDAR of derivatives for Santa Cruz County. See table 1 for a list of all the derivatives.Table 1. LiDAR derivatives for Santa Cruz CountyDatasetDescriptionLink to DatasheetLink to DataCanopy Height ModelThis depicts Santa Cruz County’s woody canopy as a Digital Elevation Model.https://vegmap.press/sc_chm_datasheethttps://vegmap.press/sc_chmNormalized Digital Surface ModelThis depicts the height above ground of objects on the earth’s surface, like trees and buildings.https://vegmap.press/sc_ndsm_datasheethttps://vegmap.press/sc_ndsmDigital Surface ModelThis depicts the elevation above sea level atop of objects on the earth’s surface.https://vegmap.press/sc_dsm_datasheethttps://vegmap.press/sc_dsm HillshadeThis depicts shaded relief based on the Digital Terrain Model. Hillshades are useful for visual reference when mapping features such as roads and drainages and for visualizing physical geography. https://vegmap.press/sc_hillshade_datasheethttps://vegmap.press/sc_hillshadeDigital Terrain ModelThis depicts topography, while removing all above-ground objects on the earth’s surface, like trees and buildings.https://vegmap.press/sc_dtm_datasheethttps://vegmap.press/sc_dtm

This dataset consists of a shapefile representing 50 foot contour intervals for Santa Cruz County, Arizona. Datasets are also available for 100', 250', and 500' intervals. Each file covers an Arizona county or part of a county and as a collection covers the entire state. The data were created by processing hillshade TIF files derived from the U.S. Geological Survey National Elevation Dataset. The processing produced ESRI formatted coverages for each county or part of a county. The U.S. Geological Survey has developed a National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. The specifications for the NED 1 arc second and 1/3 arc second data are - Geographic coordinate system, Horizontal datum of NAD83, except for AK which is NAD27, Vertical datum of NAVD88, except for AK which is NAVD29, Z units of meters.

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.

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

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

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.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

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Santa Cruz map area, California. The vector data file is included in "Habitat_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161024. Using multibeam echosounder (MBES) bathymetry and backscatter data, potential marine benthic habitat maps were constructed. The habitats were based on substrate types and documented or "ground truthed" using underwater video images and seafloor samples obtained by the USGS. These maps display various habitat types that range from flat, soft, unconsolidated sediment-covered seafloor to hard, deformed (folded), or highly rugose and differentially eroded bedrock exposures. Rugged, high-relief, rocky outcrops that have been eroded to form ledges and small caves are ideal habitat for rockfish (Sebastes spp.) and other bottom fish such as lingcod (Ophiodon elongatus). Habitat map is presented in a map format generated in a GIS (ArcMap), and both digital and hard-copy versions will be produced. Please refer to Greene and others (2007) for more information regarding the Benthic Marine Potential Habitat Classification Scheme and the codes used to represent various seafloor features. References Cited: Greene, H.G., Bizzarro, J.J., O'Connell, V.M., and Brylinsky, C.K., 2007, Construction of digital potential marine benthic habitat maps using a coded classification scheme and its application, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 141-155.

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.

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

This shapefile contains tax rate area (TRA) boundaries in Santa Cruz County for the specified assessment roll year. Boundary alignment is based on the 2022 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

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.

The POI Dataset is a digital representation of the physical, geographic and commercial features across all of Santa Clara County. This dataset aims to provide accurate location information in the map. Sources: California Department Of Education (2021), Santa Clara County Combined data (2022).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.

Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.

CDFW BIOS GIS Dataset, Contact: Melanie Gogol-Prokurat, Description: Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for California's wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California.

CDFW BIOS GIS Dataset, Contact: U.S. Fish & Wildlife Service USFWS, Description: These data identify the areas (in general) where final critical habitat for the Scotts Valley polygonum (Polygonum hickmanii) occurs. The boundaries of critical habitat for this species are coincident with the boundaries for Scotts Valley spineflower. The units of critical habitat are within the City of Scotts Valley, Santa Cruz County California.

To achieve the goals outlined in the strategic plan, the Program first must understand the current geospatial capabilities of each 9-1-1 system by individual jurisdiction. To this end, the Program hired Mission Critical Partners, LLC (MCP) to evaluate the readiness of GIS staff and data in each 9-1-1 system to support the migration to and continuing operation of NG9-1-1. The Program specifically seeks a report on the weaknesses and strengths of each 9-1-1 system throughout Arizona to frame a statewide picture for legislators as the Program seeks to fill the full-time positions necessary to fully support GIS capabilities for efficient and effective NG9-1-1 call routing.

The Santa Clara County Planning Office is part of the Department of Planning and Development. Their primary function is to plan and regulate land use and development within the unincorporated portions of Santa Clara County. Other responsibilities include policy analysis, GIS services, research and technical assistance relating to land use, housing, environmental protection, historic preservation and demographics. The Geographic Information Services Department has taken on all those activities related to GIS data and GIS process and procedures that cross organizational boundaries. Santa Clara County encompasses 15 cities and approximately 1.7 million 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.

MPA Boundary Creation:Created from a variety of source reference input. Small topological errors resolved to larger adjacent poly where necessary. Polylines may not be exact compared to source datasets necessary to resolve topological errors.Pima County:Oro ValleyDigitized from 2016 General Plan, referencing GIS linework from previous General Plan & Environmentally Sensitive Lands Project (previous TSSW project work for OV).https://www.orovalleyaz.gov/files/assets/public/documents/town-manager/general-plan/yourvoiceourfuturegeneralplan.pdfhttps://www.orovalleyaz.gov/files/assets/public/documents/town-manager/general-plan/general-plan-land-use-map.pdfAreas where OV General Plan conflicted with Marana General Plan – area had since been annexed into Marana and has included in the Marana GP polys. MaranaDigitized from Make Marana – 2040 General PlanMap atlas available at: https://static1.squarespace.com/static/54cc191ce4b0f886f4762582/t/5e50496454d84d590324e663/1582320010384/Marana+Map+Atlas+2.27.19+w_editsa.pdfSpecifically referenced Figure 1: Planning Area map dated 2/2019SahuaritaDigitized from Aspire 2035 – Sahuarity’s General Plan https://sahuaritaaz.gov/DocumentCenter/View/1169/Aspire-2035-Sahuaritas-General-Plan-Amended-2020?bidId=City of Tucson Digitized from COT Future Growth Scenario Plan .pdf https://www.tucsonaz.gov/files/integrated-planning/LT-7_Future_Growth_Scenario_Map_7-8-13.pdfPart of Plan Tucsonhttps://www.tucsonaz.gov/pdsd/plan-tucsonSanta Cruz County: **Note: The following had instances of overlapping polygons in the reference data and were left as a topological exceptions of overlapping polygons. Nogales & Patagonia General Plans, as both had the area covered in their GPs Tres Alamos General Plan & Benson GPSt David GP and Denson GPCCNogalesVerified linework from Nogales General Plan 2010http://www.azplanningcenter.com/Nogales/Files/2010_08_20-000-ExecutiveSummary_IntroductionAndOverview.pdfPatagoniaVerified linework from 2009 General Planhttps://issuu.com/seagoedd/docs/patagonia_general_plan?layout=http%253A%252F%252Fskin.issuu.com%252Fv%252Flight%252Flayout.xml&showFlipBtn=trueCochise County Created from various input GIS datasets:Comprehensive Plan Growth Areas feature classComprehensive Plan Design feature class