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FGDC CSDGM MetadataVerify - ISD GIS
Watershed Sciences, Inc. (WSI)
503-505-5100
503-546-6801
421 S.W. 6th Ave., Suite 800
Portland
OR
97204
US
20230602
ArcGIS Metadata
1.0
Sonoma County Agricultural Preservation and Open Space District
(707) 565-7369
747 Mendocino Ave, Suite 100
Santa Rosa
CA
95401
US
Lidar_Highest_Hit_DEM_2013
2014-02-19
Sonoma County Vegetation Mapping and LiDAR Program
raster digital data
The highest hit digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures included. The highest hit DEMs were derived from LiDAR data using the highest hit method to identify the tops of features. The elevation units are in meters. Some elevation units have been interpolated across areas where there are no elevation data (e.g., over water). Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average intensity for that area. The specified coordinate system for this dataset is California State Plane Zone II (FIPS 0402), NAD83 (2011), with units in US Survey Feet for horizontal, and vertical units are NAVD88 (12A) US Survey Feet. The dataset encompasses a portion of Sonoma County. WSI collected the LiDAR and created this data set for the Sonoma County Vegetation Mapping and LiDAR Consortium.
The Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) and the University of Maryland (under grant NNX13AP69G from NASA’s Carbon Monitoring System, Dr. Ralph Dubayah, PI) contracted LiDAR and orthophoto data collection for all of Sonoma County in late 2013. Also included in the data collection were two areas in Mendocino County - the Soda Spring Creek-Dry Creek Watershed and Lake Mendocino. This fine scale data will help provide an accurate, up-to-date inventory of the county’s landscape features, ecological communities and habitats. Project funders include: NASA, the University of Maryland, the Sonoma County Agricultural Preservation and Open Space District, the Sonoma County Water Agency, the California Department of Fish and Wildlife, the United States Geological Survey, the Sonoma County Information Systems Department, the Sonoma County Transportation and Public Works Department, the Nature Conservancy, and the City of Petaluma.
Sonoma County Vegetation Mapping and LiDAR Consortium, NASA, University of Maryland, Watershed Sciences, Inc., Tukman Geospatial LLC
Sonoma County, Lake Mendocino, Sonoma Lake Watershed
LiDAR, Light Detection And Ranging
LiDAR
Light Detection And Ranging
Sonoma County
Lake Mendocino
Sonoma Lake Watershed
Data were provided by the University of Maryland and the Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) under grant NNX13AP69G from NASA’s Carbon Monitoring System (Dr. Ralph Dubayah, PI). This data is available for unrestricted public use. However, users should acknowledge the source of the data in any reports, publications, or presentations where the data is used.
Data were provided by the University of Maryland and the Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) under grant NNX13AP69G from NASA’s Carbon Monitoring System (Dr. Ralph Dubayah, PI). This data is available for unrestricted public use. However, users should acknowledge the source of the data in any reports, publications, or presentations where the data is used.
Ground Condition - LiDAR: Leica ALS50 & Leica ALS70
2013-09-28
2013-11-26
-123.238581
-122.390681
38.298129
38.511668
Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388
1
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39.342439
38.086871
LiDAR flight lines have been examined to ensure that there was at least 60% sidelap, there are no gaps between flightlines, and overlapping flightlines have consistent elevation values. Shaded relief images have been visually inspected for data errors such as pits, border artifacts, gaps, and shifting. The data were examined at a 1:3000 scale.
LiDAR has been collected and processed for all areas within the project study Area. In the First-Return surface model, only the highest hits are shown (e.g. tree-tops, roofs, etc.).
Relative Accuracy measures the divergence between points from different flightlines. Relative Accuracy median is 0.05 meters (0.16 feet) out of 106,255,665,985 laser points over 4,133 flightlines. For more information regarding the internal consistency between ground-classified points from different overlapping flightlines please see LiDAR data report.
The Fundamental Vertical Accuracy (FVA) of the data set is 0.03 meters (0.09 feet). Accuracy was assessed using 9,685 ground control (real time kinematic) points. These ground control points are distributed through out the project study area. Supplemental Vertical Accuracy (SVA) is reported as the deviation between landcover classified laser points and landclass checkpoints at the 95th percentile. The SVA for individual land classes are 0.27 meters for shrub, 0.09 meters for short grass, 0.19 meters for tall grass, 0.19 meters for mixed forest, 0.05 meters for developed areas, 0.12 for herbaceous upland natural areas, 0.05 for non-natural woody areas and 0.07 for barren areas. The supplemental vertical accuracies were calculated using 417 individual landclass checkpoints. Consolidated Vertical Accuracy (CVA) is reported as the deviation between both ground and landcover classified laser points from all survey checkpoints, reported at the 95th percentile. CVA for this dataset is 0.06 meters, and was calculated from 10,102 ground and landclass checkpoints. See LiDAR data report.
The FVA was tested using 851 independent ground control points (GCPs) located in open terrain. The GCPs were distributed throughout the project area. Elevations from the unclassified LiDAR surface were measured for the x,y location of each check point. Elevations interpolated from the LiDAR surface were then compared to the elevation values of the surveyed control. The Root-Mean-Square (RMSE) was computed to be 0.03 m (0.09 ft.). AccuracyZ has been tested to meet 0.05 m (0.17 ft.) FVA at 95 Percent confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.
0.05 meters RMSEz at 95 percent Confidence Interval.
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This raster data set represents highest hit surface elevations derived from classified LiDAR point data.
Sonoma County Vegetation Mapping and LiDAR Program
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