7 WSI 20140219 Lidar point cloud This dataset describes the LiDAR missions, or lifts, which are comprised of individual swaths. Individual missions receive several types of adjustments, calculated from linear samples of flightline surface offsets (TerraSolid LiDAR software tools). The first adjustment is a global boresight, which corrects for attitude offsets resulting from inertial measurement unit configuration and scale adjustment for torsional flex of sensor material. Global per-mission adjustment magnitudes average below 0.05 degrees in heading, roll, and pitch (1-sigma values under 0.005) and less than 0.001 degree in scale (1-sigma values under 0.001). The second type of adjustment occurs in elevation, heading, roll and pitch. Corrections that accommodate line-to-line misalignments resulting from acquisition conditions, the influence of terrain variation on aircraft motion, and systematic misalignments that remain following the mission boresight. Per-flightline adjustment magnitudes average below 0.02m in elevation (1-sigma values under 0.05) and below 0.01 degrees in heading, roll, and pitch (1-sigma values under 0.002. Subsequent adjustments in elevation are highly dependant on local terrain, vegetation, and land cover conditions, as well as mission density and areal extent and configuration of study area shape. Individual missions are also evaluated for range bias against ground survey data, and adjusted positive or negative where needed. USGS-NGP Base Lidar Specification v1.0 Leica ALS 70 sensor 4 2 8 Variable 150 30 52.2 variable, dependent upon sensor, flight altitude, and SPIA or NPIA 4 0.3 nominal footprint 1064 0 0.22 418 at 900 AGL 50+ NAD 1983 (2011), California State Plane 2, FIPS Zone 0402 National Geodetic Survey (NGS) Geoid12A Untested per contract 0.05 Short grass 0.09 Tall grass 0.19 Shrub 0.27 Mixed forest 0.19 Herbaceous 0.12 1.2 3 Withheld (ignore) points were identified in these files using ASPRS class 11. Swath “overage” points are incorporated into the data set per contract. 8 1 Ground 2 Default 3 Vegetation 6 Building 7 Low points 9 Water 10 Ignored ground 11 Noise USGS-NGP Base Lidar Specification v1.0 Leica ALS 50 sensor 4 2 8 Variable 150 30 52.2 variable, dependent upon sensor, flight altitude, and SPIA or NPIA 4 0.3 nominal footprint 1064 0 0.22 418 at 900 AGL 50+ NAD 1983 (2011), California State Plane 2, FIPS Zone 0402 National Geodetic Survey (NGS) Geoid12A Untested per contract 0.03 Short grass 0.09 Tall grass 0.19 Shrub 0.27 Mixed forest 0.19 Herbaceous 0.12 1.2 3 Withheld (ignore) points were identified in these files using ASPRS class 11. Swath “overage” points are incorporated into the data set per contract. 8 1 Ground 2 Default 3 Vegetation 6 Building 7 Low points 9 Water 10 Ignored ground 11 Noise The purpose of these LiDAR data are to provide a source dataset for geospatial analysis and mapping, and the production of high resolution LiDAR derived products such as digital elevation models. The data will be used by the Sonoma County Vegetation Mapping and LiDAR Consortium (the Consortium). These classified LiDAR point cloud data were used to create Hydro-flattened Ground Surface Models, First Return Surface Models, Hydrological Breaklines, 1-foot Contours, Building Planimetrics (cartographic and building extent), Forest Metric Rasters (Canopy Height and Density) and Intensity Images (first-return, all-returns, vegetation-returns) as necessary. 20130928 20131126 Ground Condition: Leica ALS50 & Leica ALS70 Complete None planned -123.067521 -122.345272 38.304223 38.103762 None Elevation data Lidar None Sonoma County, Mendocino Lake, Dry Creek 4 None Class Time stamp Date Elevation None This dataset was contracted by the Sonoma County Vegetation Mapping and LiDAR Consortium (the Consortium), a group of public and private organizations. This dataset may be available for public distribution, information regarding the use of this dataset should be directed to the Consortium. Watershed Sciences, Inc. (WSI) physical

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Portland Oregon 97204 US 503-505-5100 IPAS TC v. 3.2; Leica ALSPP 2.75 Build #9; TerraScan v. 13, Custom WSI software; TerraMatch v. 13; TerraScan v. 13; Las Monkey v1.4.6; Windows XP Operating System; 13 GB 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. A visual qualitative assessment was performed to ensure data completeness. There are no void areas or missing data. In some areas of heavy vegetation and forest cover, there may be relatively few ground points in the LiDAR data. The raw point cloud is of good quality and data passes Fundamental Vertical Accuracy specifications. The Fundamental Vertical Accuracy (FVA) of the data set is 0.05 meters (0.18 feet). Accuracy was assessed using 873 reserved 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 0.25 meters for shrub, 0.09 meters for short grass, 0.19 meters for tall grass, 0.19 meters for mixed forest, 0.12 for herbaceous upland natural areas. The supplemental vertical accuracies were calculated using 395 individual landclass checkpoints. Consolidated Vertical Accuracy (CVA) is reported as the deviation between both ground and landcover classified laser points from all reserved survey checkpoints, reported at the 95th percentile. CVA for this dataset is 0.05 meters, and was calculated from 1,246 reserved ground and landclass checkpoints. See LiDAR data report. 0.05 meters RMSEz at 95 percent Confidence Interval. The FVA was tested using 873 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 (0.18. ft.) 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. WSI 20140219 vector digital data and tabular data Portland, OR, USA WSI disc 20140219 ground condition WSI This data source was used (along with the airborne GPS/IMU Data) for georeferencing of the LiDAR point cloud data. WSI 20140219 LiDAR derived imagery Portland, OR, USA WSI disc 20140219 ground condition WSI This data source was used to classify the LiDAR point cloud data. Lidar Pre-Processing: Airborne GPS and IMU data were merged to develop a Smoothed Best Estimate Trajectory (SBET) of the LiDAR system for each lift. Lidar data were initially calibrated using previous best parameters for this instrument and aircraft. Relative calibration was evaluated using linear samples of surface to surface matching and parameter corrections derived. Initial corrections accommodate boresight offsets coincident with IMU configuration. Subsequent corrections resolve line to line offsets remaining in the data. This was repeated iteratively until residual errors between overlapping swaths, across all project lifts, were reduced to an appropriate threshold for terrain conditions. Data were then block adjusted to match surveyed calibration control. Raw data Fundamental Vertical Accuracy (FVA) was checked using independently surveyed checkpoints. WSI 20140219 Watershed Sciences, Inc. (WSI) physical

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Portland OR 97204 US 503-505-5100 503-546-6801 Lidar Post-Processing: The calibrated and controlled LiDAR swaths were processed using automatic point classification routines in proprietary software. These routines operate against the entire collection (all swaths, all lifts), eliminating character differences between files. Data were then distributed as virtual tiles to experienced LiDAR analysts for localized automatic classification, manual editing, and peer-based QC checks. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project area. All classification tags are stored in the original swath files. Comprehensive QA/QC was performed and accuracy and resolution statistics were derived. WSI 20140219 Watershed Sciences, Inc. (WSI) physical

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Portland OR 97204 US 503-505-5100 503-546-6801 Point Point 106,255,665,985 NAD 1983 (2011)State Plane California FIPS 0402 38.33333333 39.83333333 -122.0 37.66666667 6561666.66666667 1640416.66666667 coordinate pair 0.000000027039137595608057 0.000000027039137595608057 foot_us D NAD 1983 2011 GRS 1980 6378137.0 298.257222101 This LiDAR point cloud represents ground surface and land cover conditions at the time of acquisition WSI Sonoma County Agricultural Preservation and Open Space District mailing and physical address

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Santa Rosa CA 95401 US Not Available This dataset was contracted by the Sonoma County Vegetation Mapping and LiDAR Consortium (the Consortium), a group of public and private organizations. This dataset may be available for public distribution, information regarding the use of this dataset should be directed to the Consortium. 20140219 Watershed Sciences, Inc. (WSI) physical

421 SW 6th Ave., Suite 800

Portland OR 97204 US 503-505-5100 503-546-6801 FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998