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(WSI) 503-505-5100 503-546-6801 421 S.W. 6th Ave., Suite 800 Portland OR 97204 US 20210604 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_HydroFlat_BareEarth_DEM_2013_WM 2014-02-19 Sonoma County Vegetation Mapping and LiDAR Program raster digital data <div style='text-align:Left;'><div><div><p><span>A bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using triangulated irregular network (TIN) processing of the ground point returns. Hydro-flattened Bare Earth DEMs represent water bodies in a cartographically and aesthetically pleasing manner, and are not intended to accurately map water surface elevations. In a Hydro-flattened DEM, water surfaces are flat and level for lakes with a greater area than two acres, and gradated for rivers or other long impoundments (e.g., reservoirs) that are wider than 100 feet, and tidal areas. Any existing island larger than one acre was be delineated. Water surface edge elevations were at or below the immediately surrounding terrain. Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average elevation 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.</span></p></div></div></div> The Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) and the University of Maryland (under grant NNX13AP69G from NASA’s Carbon... 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. <div style='text-align:Left;'><div><div><p><span>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.</span></p></div></div></div> 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 10.7.1.11595 1 -123.565035 -122.224632 39.342444 38.086873 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 some areas of heavy vegetation and forest cover, there may be relatively few ground points in the LiDAR data. Some elevation units have been interpolated across areas in the ground model where there are no elevation data (e.g., over water, over dense vegetation). TINing the points produces large triangles and hence the elevations may be less accurate within such areas. Some elevation units have been interpolated across areas in the ground model where there are no elevation data (e.g., over water, over dense vegetation). Relative Accuracy measures the divergence between points from different flightlines. Relative Accuracy median is 0.05 meters (0.17 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 was compiled to meet 0.03 meters (0.09 feet). Accuracy was assessed using 9,685 survey ground check points. These ground check points are distributed through out the project study area. 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.). Using withheld ground checkpoints, vertical accuracy 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. Breaklines were created by WSI for the Hydro-flattened Bare Earth raster dataset. Hydro Breaklines breaklines 2014-02-19 WSI Ground Condition - Hydro Breaklines 2013-09-28 2013-11-26 Acquisition. LiDAR data acquisition was started September 28, 2013 and was completed on November 26, 2013. The survey is utilizing a Leica ALS50 or ALS70 laser system mounted in a Piper Navajo PA-31-325 or Cessna Caravan 208B. Near nadir scan angles were used to increase penetration of vegetation to ground surfaces. Ground level GPS and aircraft IMU were collected during the flight. 2014-02-19 Hydro-Flattening. The bare-earth DEMs were created by triangulating all ground classified points and inserting 3-D breaklines by utilizing Terra-Solid’s TerraScan and TerraModeler software. Any ground points within one meter of the breaklines were reclassified to “ignored-ground” (ASPRS code: 10) before triangulation. The highest-hit DEMs were generated from “ground” and “default” classified points. In instances where “water” classified points had the highest elevation value, the water surface elevation from the bare-earth raster were used. 2014-02-19 LiDAR Data Processing. Flight lines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. Laser point return coordinates were computed using ALS Post Processor software and IPAS Pro GPS/INS software, based on independent data from the LiDAR system, IMU, and aircraft. The raw LiDAR file was assembled into flight lines per return with each point having an associated x, y, and z coordinate. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment. Custom algorithms were designed to evaluate points between adjacent flight lines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll and yaw offset parameters optimize internal consistency. Noise (e.g., pits and birds) was filtered using ALS post-processing software, based on known elevation ranges and included the removal of any cycle slips. Using TerraScan and MicroStation, ground classifications utilized custom settings appropriate to the study area. The corrected and filtered return points were compared to the RTK ground survey points collected to verify the vertical and horizontal accuracies. Points were output as laser points, TINed and GRIDed surfaces. 2014-02-19 2 1 0 -13755196.748793 4591705.359411 -13755196.748793 4770843.078486 -13605983.743967 4770843.078486 -13605983.743967 4591705.359411 -13680590.246380 4681274.218948 163181 0.914402 195907 0.914402 This raster data set represents ground surface and hydro-flattened water surface elevations derived from ground classified LiDAR point data. 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