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

The Map Books consist of approximately 5,900 maps recorded with the county dating from circa 1850 to 1957. Recorded documents include subdivisions, surveys of property, cemetery plans, and other maps. Information on each map includes date recorded, person recorded for, and title of survey. Additional information may include notarized statement by property owner, statement by licensed surveyor, notice of approval by board of supervisors, and additional approvals by county or city officials. These maps are bound into 108 volumes. The archives have volumes A through Z, and volumes 1 through 82. Volumes not included are 44, 46, 48, 50, 51, 53, 55, 57, 59, 66, 68, 71, 73, 76, and 81.

Methods: The 2-foot resolution raster was produced from a ground classified 2020 Quality Level 1 lidar point cloud. This DSM was derived by Sanborn and Tukman Geospatial using the following process:QL1 airborne lidar point cloud collected countywide (Sanborn)Point cloud classification to assign ground points (Sanborn)First return points were used to create over 8,000 1-foot resolution hydro-flattened Raster DSM tiles. Using automated scripting routines within LP360, a GeoTIFF file was created for each tile. Each 2,500 x 2,500 foot tile was reviewed using Global Mapper to check for any surface anomalies or incorrect elevations found within the surface. (Sanborn)1-foot hydroflattened DSM tiles mosaicked together into a 1-foot resolution mosaiced hydroflattened DSM geotiff (Tukman Geospatial)1-foot hydroflattened DSM (geotiff) resampled to 2-foot hydro-flattened DSM using Bilinear interpolation and clipped to county boundary with 250-meter buffer (Tukman Geospatial)2-foot hydroflattened raster DEM (geotiff) posted on ArcGIS Online (Tukman Geospatial) The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane, Feet and vertical datum of NAVD88 (GEOID18), Feet. Lidar was collected in early 2020, while no snow was on the ground and rivers were at or below normal levels. To postprocess the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Sanborn Map Company, Inc., utilized a total of 25 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area.An additional 125 independent accuracy checkpoints, 70 in Bare Earth and Urban landcovers (70 NVA points), 55 in Tall Grass and Brushland/Low Trees categories (55 VVA points), were used to assess the vertical accuracy of the data. These check points were not used to calibrate or post process the data.Uses and Limitations:The DSM provides a raster depiction of the first (surface) returns for each 2x2 foot raster cell across Santa Clara County. The DSM 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 Clara County. See table 1 for a list of all the derivatives. Table 1. lidar derivatives for Santa Clara CountyDatasetDescriptionLink to DataLink to DatasheetCanopy Height ModelPixel values represent the aboveground height of vegetation and trees.https://vegmap.press/clara_chmhttps://vegmap.press/clara_chm_datasheetCanopy Height Model – Veg Returns OnlySame as canopy height model, but does not include lidar returns labelled as ‘unclassified’ (uses only returns classified as vegetation)https://vegmap.press/clara_chm_veg_returnshttps://vegmap.press/clara_chm_veg_returns_datasheetCanopy CoverPixel values represent the presence or absence of tree canopy or vegetation greater than or equal to 15 feet tall.https://vegmap.press/clara_coverhttps://vegmap.press/clara_cover_datasheetCanopy Cover – Veg Returns OnlySame as canopy height model, but does not include lidar returns labelled as ‘unclassified’ (uses only returns classified as vegetation)https://vegmap.press/clara_cover_veg_returnshttps://vegmap.press/clara_cover_veg_returns_datasheet HillshadeThis depicts shaded relief based on the Hillshade. Hillshades are useful for visual reference when mapping features such as roads and drainages and for visualizing physical geography. https://vegmap.press/clara_hillshadehttps://vegmap.press/clara_hillshade_datasheetDigital Terrain ModelPixel values represent the elevation above sea level of the bare earth, with all above-ground features, such as trees and buildings, removed. The vertical datum is NAVD88 (GEOID18).https://vegmap.press/clara_dtmhttps://vegmap.press/clara_dtm_datasheetDigital Surface ModelPixel values represent the elevation above sea level of the highest surface, whether that surface for a given pixel is the bare earth, the top of vegetation, or the top of a building.https://vegmap.press/clara_dsmhttps://vegmap.press/clara_dsm_datasheet

City of Santa Clara Public Safety Map. A map of fire stations and police stations around the City of Santa Clara.Organization: City of Santa Clara. If you have questions about the City of Santa Clara's ArcGIS Online web maps and applications, please contact the GIS Team at 408-615-2083 or send us an e-mail at geosupport@santaclaraca.gov.

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 herbaceo

This map shows community feedback we received during the outreach phase of the neighborhood plan process in 2017. Each point represents a comment provided by a participant about what they valued or hoped for the future of the River Road and Santa Clara neighborhoods. Comments that were not associated with a specific location are not included in this map but are available in the Reaching Out section of the River Road and Santa Clara Neighborhood Plan Project Library website.

Western Foundation of Vertebrate Zoology contracted Stillwater Sciences in 2018 to create a fine-scale vegetation map of portions of the Santa Clara River. The mapping study area, consists of approximately 16,370 acres of Ventura County. Work was performed on the project during the summer and fall of 2018. The projects main goal was to address the need for detailed up-to-date vegetation information in support of identifying and modeling habitat for southwestern willow flycatcher, yellow-billed cuckoo, and least Bell's vireo. Funding for the project was provided by an Endangered Species Act Section 6 grant from the United States Fish and Wildlife Service to the California Department of Fish and Wildlife. This project builds off a prior mapping project that was conducted by Stillwater Sciences and URS, which was funded by the California State Coastal Conservancy and the Santa Clara River Trustee Council, in 2007. Species composition data collected in the field was compiled and reviewed in the office to assign the appropriate MCV alliance to each sampled location. In cases where the species present were best described by an MCV association (a sub-category of the broader MCV alliance), one was assigned. For field sampled locations with unique species composition not currently represented by an existing MCV alliance or association, a provisional alliance or association was created. In addition, some areas were classified into broader land cover types (e.g., agriculture, developed, riverwash). The vegetation map was produced applying digital aerial imagery (natural color, 2-foot resolution) from the National Agricultural Imagery Program (NAIP) (USDA-FSA 2016) flown in May, June, and July 2016. The minimum mapping unit (MMU) is 0.5 acres for most types and 0.1 for more unusual types that were discernable from areal photography and/or documented in the field. Once the map was made photointerpretation of the NAIP imagery took place in order to identify vegetation types. Field mapping took place after to refine the vegetation type definitions, CNPS vegetation reconnaissance field forms were used in the field. There was a total of 91 mapping classes. There was no accuracy assessment was done for this project. 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/2900_2999/ds2961.zip

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

Contains the sub-addresses within the City of Santa Clara. View on MapSantaClara: https://map.santaclaraca.gov

This record is maintained in the National Geologic Map Database (NGMDB). The NGMDB is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information, developed according to standards defined by the cooperators, i.e., the USGS and the Association of American State Geologists (AASG). Included in this system is a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 90,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies. For more information, please see http://ngmdb.usgs.gov/.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

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.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

Methods:This lidar derivative provides information about the bare surface of the earth. The 2-foot resolution hillshade raster was produced from the 2020 Digital Terrain Model using the hillshade geoprocessing tool in ArcGIS Pro.QL1 airborne lidar point cloud collected countywide (Sanborn)Point cloud classification to assign ground points (Sanborn)Ground points were used to create over 8,000 1-foot resolution hydro-flattened Raster DSM tiles. Using automated scripting routines within LP360, a GeoTIFF file was created for each tile. Each 2,500 x 2,500 foot tile was reviewed using Global Mapper to check for any surface anomalies or incorrect elevations found within the surface. (Sanborn)1-foot hydroflattened DTM tiles mosaicked together into a 1-foot resolution mosaiced hydroflattened DTM geotiff (Tukman Geospatial)1-foot hydroflattened DTM (geotiff) resampled to 2-foot hydro-flattened DTM using Bilinear interpolation and clipped to county boundary with 250-meter buffer (Tukman Geospatial)2-foot hillshade derived from DTM using the ESRI Spatial Analyst ‘hillshade’ function The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane, Feet and vertical datum of NAVD88 (GEOID18), Feet. Lidar was collected in early 2020, while no snow was on the ground and rivers were at or below normal levels. To postprocess the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Sanborn Map Company, Inc., utilized a total of 25 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 125 independent accuracy checkpoints, 70 in Bare Earth and Urban landcovers (70 NVA points), 55 in Tall Grass and Brushland/Low Trees categories (55 VVA points), were used to assess the vertical accuracy of the data. These check points were not used to calibrate or post process the data.Uses and Limitations: The hillshade provides a raster depiction of the ground returns for each 2x2 foot raster cell across Santa Clara County. The layer is useful for hydrologic and terrain-focused analysis and is a helpful basemap when analyzing spatial data in relief.Related Datasets: This dataset is part of a suite of lidar of derivatives for Santa Clara County. See table 1 for a list of all the derivatives. Table 1. lidar derivatives for Santa Clara CountyDatasetDescriptionLink to DataLink to DatasheetCanopy Height ModelPixel values represent the aboveground height of vegetation and trees.https://vegmap.press/clara_chmhttps://vegmap.press/clara_chm_datasheetCanopy Height Model – Veg Returns OnlySame as canopy height model, but does not include lidar returns labelled as ‘unclassified’ (uses only returns classified as vegetation)https://vegmap.press/clara_chm_veg_returnshttps://vegmap.press/clara_chm_veg_returns_datasheetCanopy CoverPixel values represent the presence or absence of tree canopy or vegetation greater than or equal to 15 feet tall.https://vegmap.press/clara_coverhttps://vegmap.press/clara_cover_datasheetCanopy Cover – Veg Returns OnlySame as canopy height model, but does not include lidar returns labelled as ‘unclassified’ (uses only returns classified as vegetation)https://vegmap.press/clara_cover_veg_returnshttps://vegmap.press/clara_cover_veg_returns_datasheet HillshadeThis depicts shaded relief based on the Hillshade. Hillshades are useful for visual reference when mapping features such as roads and drainages and for visualizing physical geography. https://vegmap.press/clara_hillshadehttps://vegmap.press/clara_hillshade_datasheetDigital Terrain ModelPixel values represent the elevation above sea level of the bare earth, with all above-ground features, such as trees and buildings, removed. The vertical datum is NAVD88 (GEOID18).https://vegmap.press/clara_dtmhttps://vegmap.press/clara_dtm_datasheetDigital Surface ModelPixel values represent the elevation above sea level of the highest surface, whether that surface for a given pixel is the bare earth, the top of vegetation, or the top of a building.https://vegmap.press/clara_dsmhttps://vegmap.press/clara_dsm_datasheet

This record is maintained in the National Geologic Map Database (NGMDB). The NGMDB is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information, developed according to standards defined by the cooperators, i.e., the USGS and the Association of American State Geologists (AASG). Included in this system is a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 90,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies. For more information, please see http://ngmdb.usgs.gov/.

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

no abstract provided

lts coded road network for santa clara county

description: This digital map database, compiled from previously open- filed U.S. Geological Survey reports (Graymer and others, 1994, Graymer, Jones, and Brabb, 1994) and unpublished data, represents the general distribution of rocks and faults in the Hayward fault zone. As described in this report, the Hayward fault zone is a zone of highly deformed rocks which trends north 30 degrees west from an area southeast of San Jose to the San Pablo Bay, and ranges in width from 2 to 10 kilometers. Although historic earthquake activity has been concentrated in the western part of the zone, the zone as a whole reflects oblique right-lateral and compressive deformation along a significant upper crustal break over the past 10 million years or more. Together with the accompanying text file (hfgeo.txt), the database provides current information on the distribution and description of faults and rock types within the fault zone. In addition, the text file discusses the development of the fault zone in the past 10 million years, the relationship of the Hayward and Calaveras fault zones, and the significance of the creeping strand of the Hayward fault (as most recently defined by Lienkaemper, 1992).; abstract: This digital map database, compiled from previously open- filed U.S. Geological Survey reports (Graymer and others, 1994, Graymer, Jones, and Brabb, 1994) and unpublished data, represents the general distribution of rocks and faults in the Hayward fault zone. As described in this report, the Hayward fault zone is a zone of highly deformed rocks which trends north 30 degrees west from an area southeast of San Jose to the San Pablo Bay, and ranges in width from 2 to 10 kilometers. Although historic earthquake activity has been concentrated in the western part of the zone, the zone as a whole reflects oblique right-lateral and compressive deformation along a significant upper crustal break over the past 10 million years or more. Together with the accompanying text file (hfgeo.txt), the database provides current information on the distribution and description of faults and rock types within the fault zone. In addition, the text file discusses the development of the fault zone in the past 10 million years, the relationship of the Hayward and Calaveras fault zones, and the significance of the creeping strand of the Hayward fault (as most recently defined by Lienkaemper, 1992).