These are locations that are to be used as an elevation reference and contain the official elevation and last known latitude and longitude. App: The data can be viewed in web map format at: Survey BenchmarksData is published on Mondays on a weekly basis.

This is a ~31 GB RAR file that contains a file gdb. LiDAR collected in late 2022.Product: These are one foot contour data as part of the required deliverables for the lidar project. Also delivered were 5, 10, and 25 foot contour subsets. Geographic Extent: Alameda, Merced, Monterey, San Benito, San Joaquin, San Mateo, Santa Clara, Santa Cruz, and Stanislaus counties, California, covering approximately 1769 square miles. Dataset Description: The lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification. The data was developed based on a horizontal projection/datum of NAD83(2011) California Zone 3, Feet and vertical datum of NAVD88 (GEOID18), Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 8185 individual 2500 ft x 2500 ft tiles clipped to the DPA, as tiled intensity images, as tiled DTMs, as tiled DEMs, and as tiled DSMs; all tiled to the same 2500 ft x 2500 ft schema. Ground Conditions: Lidar was collected in late 2022, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Sanborn Map Company, Inc., established a total of 42 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 129 independent accuracy check points, 74 in bare earth and urban landcovers (74 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.

The Social Vulnerability Index (SVI) indicates the relative overall vulnerability of every U.S. Census tract within Santa Clara County based on 14 social factors as developed by the Center for Disease Control. Derived primarily from U.S. Census American Community Survey 5 yr data 2012-2016 in 2018.

Product: These are 2D data as part of the required deliverables for the lidar project. Geographic Extent: Santa Clara county, California, covering approximately 1771 square miles. Dataset Description: The lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 2.1. The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane, Feet and vertical datum of NAVD88 (GEOID18), Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 8185 individual 2500 ft x 2500 ft tiles, as tiled intensity rasters, and as tiled bare-earth DEMs; all tiled to the same 2500 ft x 2500 ft schema. Ground Conditions: Lidar was collected in early 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process 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.

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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.

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 8183 individual 2500 ft x 2500 ft tiles; used to create intensity rasters, 3D breaklines and hydro-flattened DEMs as necessary. Geographic Extent: Santa Clara county, California, covering approximately 1771 square miles. Dataset Description: The lidar project called for the Planning, Acquisition, processing and deriv...

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