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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
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TwitterGeospatial data about Santa Cruz County, California Parcels. Export to CAD, GIS, PDF, CSV and access via API.
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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/ds3116.zip.
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TwitterThis 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.
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TwitterTo 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.
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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
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TwitterThe 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.
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TwitterThe 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.
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TwitterCDFW 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.
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TwitterThis polyline shapefile contains an extract of selected geographic and cartographic information, including water, railroad and road features, for the County of Santa Cruz, California from the United States Census Bureau Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB) for 2011. The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Edge refers to the linear topological primitives that make up MTDB. This "All Lines" shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the "All Lines" shapefile are available in relational (.dbf) files that users must download separately. The "All Lines" shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value. This layer is part of a collection of GIS data created for Santa Cruz County, California.
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TwitterThis polyline shapefile contains an extract of selected geographic and cartographic information, including water, railroad and road features, for the County of Santa Cruz, California from the United States Census Bureau Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB) for 2010. The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Edge refers to the linear topological primitives that make up MTDB. This "All Lines" shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the "All Lines" shapefile are available in relational (.dbf) files that users must download separately. The "All Lines" shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value. This layer is part of a collection of GIS data created for Santa Cruz County, California.
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TwitterIn 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/16c49a65-baae-4ef4-a2be-32655fce18ab for complete metadata about this dataset.
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TwitterIn 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.
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TwitterThe 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.
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TwitterThe 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.
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TwitterThe 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.
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Land-use zoning districts in the unincorporated areas of Santa Cruz County, California. These zoning districts are intended to promote specific land use policies in order to implement goals identified in Santa Cruz County's General Plan and Local Coastal Plan.
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TwitterThe 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.
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TwitterCity of Santa Cruz General Plan 2030 Land Use.
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TwitterThe 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.
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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