7 WSI 20140225 LiDAR point cloud This dataset is a LiDAR point cloud, which encompasses the Sonoma County Vegetation Mapping and LiDAR Program's project area (all of Sonoma County and small areas of southern Mendocino County). This dataset consists of 11,035 LiDAR point cloud .LAS files. Each .LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. Each file represents a separate tiled 2,100 feet by 2,100 feet area of coverage.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. 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. The three-dimensional polygon (PolygonZ) dataset represents water bodies that were hydro-flattened in accordance with the LiDAR Base Specifications Version 1.0 (USGS, 2012). These polylines were inserted as hard breaklines in the creation of the associated Hydro-Flattened Bare Earth rasters. Elevation values are recorded in meters. Watershed Sciences, Inc. collected the LiDAR near Farmington, UT in Davis County and created this data set for the State of Utah AGRC. 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.Ground Conditions: water at normal levels; no unusual inundation; mainly leaf off. The University of Maryland (under grant NNX13AP69G from NASA’s Carbon Monitoring System, Dr. Ralph Dubayah and Dr. George Hurtt, PIs) contracted LiDAR and orthophoto data collection for all of Sonoma County in late 2013 to support countywide forest carbon mapping. The Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) funded a suite of LiDAR derived products and additional LiDAR collection in 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. USGS-NGP Base Lidar Specification v1.0 Leica ALS 70 sensor 4 2 8 900 150 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 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 20131109 20131126 Ground Condition: Leica ALS50 & Leica ALS70 Complete None planned -123.157217 -122.538149 38.918823 38.506608 None Elevation data Lidar None Sonoma County, Mendocino Lake, Dry Creek 4 None Class Time stamp Date Elevation None LiDAR data and orthophotography were provided by the University of Maryland under grant NNX13AP69G from NASA's Carbon Monitoring System (Dr. Ralph Dubayah and Dr. George Hurtt, Principal Investigators). This grant also funded the creation of derived forest cover and land cover information, including a countywide biomass and carbon map, a canopy cover map, and DEMs. The Sonoma County Vegetation Mapping and LiDAR Program funded LiDAR derived products in the California State Plane Coordinate System, such as DEMs, hillshades, building footprints, 1-foot contours, and other derived layers. The entirety of this data is freely licensed for unrestricted public use, unless otherwise noted. Any use of these data, including value-added products, within reports, papers, and presentations must acknowledge NASA Grant NNX13AP69G, the University of Maryland, and the Sonoma Vegetation Mapping and LiDAR Program as their sources. Watershed Sciences, Inc. (WSI) physical

421 SW 6th Ave., Suite 800

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 was compiled to meet 0.05 meters (0.17 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 0.96 US Feet for Shrub, 0.44 US Feet for short grass, 0.77 US Feet for tall grass, 0.68 US Feet for forest, 0.45 US Feet for crops, and 0.18 US Feet for Urban. The supplemental vertical accuracies were calculated using 420 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 0.410 US Feet, and was calculated from 1268 ground and landclass checkpoints. See LiDAR data report. 0.05 meters RMSEz at 95 percent Confidence Interval. The FVA was tested using 848 independent ground control points (GCP's) 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 0.03m. AccuracyZ has been tested to meet 0.05m 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. WSI 20140225 vector digital data and tabular data Portland, OR, USA WSI disc 20131126 ground condition WSI This data source was used (along with the airborne GPS/IMU Data) for georeferencing of the LiDAR point cloud data. WSI 20131122 LiDAR derived imagery Portland, OR, USA WSI disc 20140225 ground condition WSI This data source was used to classify the LiDAR point cloud data. - 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. 20141024 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 20140225 Watershed Sciences, Inc. (WSI) physical

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Portland OR 97204 US 503-505-5100 503-546-6801 1. LiDAR points sampled to arrive at an elevation threshold defining the water surface at the time of acquisition. 2. Generalized three dimensional polylines were created to encompass all areas considered to be water and assigned the water surface elevation value. 3. Centerlines were digitized for all water surfaces not perceived as “flat” then given z values. 4. A bounding polygon was created around the water points with all discontinuities (e.g., bridges, overhanging vegetation, etc.) removed. Z-values were applied to the bounding polygon based on the elevation values of the associated centerlines. 5. The bare-earth DEMs were created by triangulating all “ground” classified points and inserting 3-D breaklines utilizing TerraSolid’s TerraScan and TerraModeler software. 20140219 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 20140225 Watershed Sciences, Inc. (WSI) physical

421 SW 6th Ave., Suite 800

Portland OR 97204 US 503-505-5100 503-546-6801 Point Point 106,255,665,985 NAD 1983 StatePlane California II FIPS 0402 USFeet 2011 38.33333333333334 39.83333333333334 -122.0 37.66666666666666 6561666.666666666 1640416.666666667 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

747 Mendocino Ave, Suite 100

Santa Rosa CA 95401 US (707) 565-7369 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. 20140225 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