20200323 15041500 1.0 FALSE Russian_River_Mark_West_Depth_Raster_48ft 6236126.396389 6419885.396389 1816123.543629 2075767.543629 1 002 Projected GCS_NAD_1983_2011 Linear Unit: Foot_US (0.304801) NAD_1983_2011_StatePlane_California_II_FIPS_0402_Ft_US <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.7'><WKT>PROJCS[&quot;NAD_1983_2011_StatePlane_California_II_FIPS_0402_Ft_US&quot;,GEOGCS[&quot;GCS_NAD_1983_2011&quot;,DATUM[&quot;D_NAD_1983_2011&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,6561666.666666666],PARAMETER[&quot;False_Northing&quot;,1640416.666666667],PARAMETER[&quot;Central_Meridian&quot;,-122.0],PARAMETER[&quot;Standard_Parallel_1&quot;,38.33333333333334],PARAMETER[&quot;Standard_Parallel_2&quot;,39.83333333333334],PARAMETER[&quot;Latitude_Of_Origin&quot;,37.66666666666666],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,6418]]</WKT><XOrigin>-115211800</XOrigin><YOrigin>-93821500</YOrigin><XYScale>36983428.057351544</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>103004</WKID><LatestWKID>6418</LatestWKID></ProjectedCoordinateSystem> 32 FALSE None 1 AIG TRUE continuous floating point -3.4028235e+038 20230106 14135400 20260121 7244400 150000000 5000 FGDC Quantum Spatial 503-505-5100 421 SW 6th Ave #800 Portland OREGON 97204 US 20260121 ArcGIS Metadata 1.0 Shelly Bianchi-Williamson Sonoma County 2550 Ventura Avenue Santa Rosa California 95403 Shelly.Bianchi-Williamson@sonoma-county.org File Geodatabase Raster Dataset Russian_River_Mark_West_Depth_Raster_48ft 2020-03-20 Quantum Spatial raster data <div style='text-align:Left;'><div><div><p><span>The Sonoma County Russian River - Mark West Creek Inundation Model provides high resolution water depth data. The water depth digital elevation model (DEM) represents the difference between water surface elevation models and bare earth (all vegetation and man-made structures removed) digital elevation models. The water surface elevations were estimated using HEC RAS 5.0.7 hydrologic modeling software. Each pixel is three feet by three feet and represents an average height above ground for that area. QSI collected the LiDAR and created this data set for the Russian River Modeling and Buildings study area. The projection is CASP 2 with horizontal datum NAD83(2011), vertical datum NAVD88 (Geoid 12A), and the units are US Survey Feet. See Process Steps for derivation of raster datasets.</span></p><p><span /></p><p><span /></p></div></div></div> The water depth digital elevation model (DEM) represents inundation at the specified extent, as depicted in the Sonoma County Russian River - Mark West Creek Inundation Model. Data to be used for planning and emergency evacuation. Sonoma County Shelly Bianchi-Williamson Sonoma County 2550 Ventura Avenue Santa Rosa CA 95403 Shelly.Bianchi-Williamson@sonoma-county.org California Sonoma County ISO 19115 Topic Categories location boundaries Water Surface Elevation Digital Terrain Model Hydrology LiDAR Flood Depth Flood Inundation Raaster Water Depth Water Surface Elevation California location Sonoma County Digital Terrain Model Hydrology LiDAR Flood Depth Flood Inundation Raaster Water Depth boundaries Please contact Sonoma County for information regarding the use of this data. <div style='text-align:Left;'><div><div><p><span>Please contact Sonoma County for information regarding the use of this data.</span></p></div></div></div>, None. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. <div style='text-align:Left;'><div><div><p><span>Please contact Sonoma County for information regarding the use of this data.</span></p></div></div></div>, None. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595 -123.133691 -122.713223 38.33358 38.857612 Sonoma County 2020-03-21 Raster File Type = GRID Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 3 feet Interpolation or Resampling Technique = Triangulated Irregular Network (TIN), Linear Interpolation, Proprietary 1 -123.143247 -122.492988 38.860995 38.143544 Water features are derived from hydrologic model results and delineated from LiDAR data collected throughout the defined study area. Feature completeness is representative of the time period of data acquisition. The study area was defined by Sonoma County. QSI performed a hydrological analysis and generated resulting data throughout the defined study area. LAS Point Classification: The point classification is performed as described below. The bare earth surface is manually reviewed to ensure correct classification on the Class 2 (Ground) points. All data were manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. ArcMap is used as a final check of the bare earth dataset. TerraScan, LasTools, and Las Monkey was then used to create the deliverable industry-standard LAS files for both the All Point Cloud Data and the Bare Earth. Quantum Spatial, Inc. proprietary software was used to perform final statistical analysis of the classes in the LAS files, on a per tile level to verify final classification metrics and full LAS header information. 2018-01-01 Raw Data and Boresight Processing: The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technicians first used Quantum Spatial, Inc. proprietary and commercial software to calculate initial boresight adjustment angles based on sample areas selected in the lift. These areas cover calibration flight lines collected in the lift, cross tie and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technician then analyzed the results and made any necessary additional adjustment until it is acceptable for the selected areas. 3) Once the boresight angle calculation was completed for the selected areas, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technicians utilized commercial and proprietary software packages to analyze how well flight line overlaps match for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once all lifts were completed with individual boresight adjustment, the technicians checked and corrected the vertical misalignment of all flight lines and also the matching between data and ground truth. The relative accuracy was less than or equal to 7 cm RMSEz within individual swaths and less than or equal to 10 cm RMSEz or within swath overlap (between adjacent swaths). 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed check points after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level (Required Accuracy) was met. 2019-01-01 Hydro depth raster DEM Processing: Hydro depth rasters were generated by subtracting the bare earth DEM from the water surface elevation DEM output from the HEC RAS modeling process 2020-01-01 QSI derived water surface shapes from a bare earth DEM created from the classified LiDAR point cloud and the results of hydrological modeling. Water surface elevations were simulated using HEC RAS 5.0.7 and output as polygon shapefiles. The resulting flood extent polygon shapefiles were created by comparing the modeled water surface elevation to the bare earth elevation as measured in the bare earth DEM. 2020-03-20 Data covers the entire area specified for this project. LiDAR were collected and processed for the entire project study area during a previous LiDAR collection. In some areas of heavy vegetation and forest cover, there may be relatively few ground points in the LiDAR data. TINing the points produces large triangles and hence the elevations may be less accurate within such areas. In some areas with large bodies of water, competing water surface levels may be visible. This is due to seasonal water level fluctuation and intervals of time between acquisition of an area. Ground survey data were acquired as part of the original LiDAR collection for Sonoma County. A subset of these points were reserved for non-vegetated vertical accuracy testing. The Bare Earth DEM NVA was tested with these reserved lidar data points located in bare earth (non-vegetated) areas. See the data report for methodology, descriptive statistics, and relevant standards and reporting language. The root mean square error (RMSE) of the native LiDAR point cloud data used in the creation of the bare earth DEM used to calculate this depth raster is 0.03 meters. Accuracy was assessed using ground check points (GCPs). These GCPs are distributed throughout the study area. See previous LiDAR data report. 0.03 86548 3.000000 61253 3.000000 2 1 0 6236126.396389 1816123.543629 6236126.396389 2075767.543629 6419885.396389 2075767.543629 6419885.396389 1816123.543629 6328005.896389 1945945.543629 dataset EPSG 8.9.3(10.3.1) Band_1 172.268051 0.000999 32 Pixel 86548 61253 3.000000 3.000000 32 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE row and column 3.000000 3.000000 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