001 Sonoma County Vegetation Mapping and LiDAR Program 20140321 remote-sensing image These data are LiDAR orthorectified aerial photographs (8-bit GeoTIFF format) within the Sonoma County Vegetation Mapping and LiDAR Program's project area. Imagery was collected in fall, 2013. The imagery coverage corresponds to the Sonoma County 2013 LiDAR survey data extent and encompasses approximately 1,047,999 acres. A GSD (Ground Sample Distance) resolution of 6 inches was used for each four-band color pixel. WSI recommends viewing the orthoimagery in ESRI ArcMap software using a raster catalog. For best results, stretch type should be set to 'None' and Gamma Stretch should not be applied (Layer Properties -> Symbology Tab). The specified coordinate system for this dataset is California State Plane Zone II (FIPS 0402), NAD83 (2011), with units in US Survey Feet. 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. 20131001 20131028 Ground condition during daylight hours orthophoto survey - UltraCam Eagle 260 megapixel camera Complete None planned -123.548077 -122.345272 39.246035 38.098597 None Sonoma County, WSI, Airborne Survey, Light Detection and Ranging, LiDAR Rectified Orthophotographs, Ortho, Digital Orthophoto, Orthophotography, high resolution color imagery, color infrared, CIR, NIR, near-infrared, aerial photographs ISO 19115 Topic Categories imageryBaseMapsEarthCover None Sonoma County, Mendocino Lake, Dry Creek 1 None Aerial imagery 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. Sonoma County Vegetation Mapping and LiDAR Consortium, NASA, University of Maryland, Watershed Sciences, Inc., Tukman Geospatial LLC Flight lines have been examined to ensure that there was at least 60% sidelap, there are no gaps between flight lines, and overlapping flight lines have consistent elevation values. All orthophotographs have been processed and reviewed for contracted accuracy and completeness. Orthophoto mosaics were reviewed at a scale of 1:2000 and reviewed against the LiDAR intensities to ensure no seam artifacts or offsets. Raw acquired images were radiometrically and geometrically corrected using the camera’s calibration files. The resulting radiometry is then manually edited by digitally adjusting output levels, exposure and intensity, atmospheric haze correction, and applying hotspot dodging. This ensures that each image has the appropriate tone, no pixels are clipped, and that each image frame is blended with its neighbors. Once radiometry has been edited, separate RGBI and Panchromatic images are blended together to form single pan-sharpened 4 band TIFF images. During the mosaicking stage, orthorectified frames are color balanced a second time using an automated global tilting method and in certain cases, further manual balancing. Despite these extensive radiometric blending techniques, occasional frame to frame radiometric discrepancy may exist within the final mosaics due to bi-directional solar reflectance, changing sun angle, or difficult atmospheric conditions. To assess the spatial accuracy of the orthophotographs, they were compared against check points identified from the LiDAR intensity images. The checkpoints were distributed evenly across the total acquired area, and were measured on surface features such as painted road lines and fixed high-contrast objects on the ground surface. Horizontal accuracy applies only to the portion of the swath that was orthorectified to the LiDAR-derived DEM. Outside of that, accuracy and radiometry at ortho seams are not guaranteed. The accuracy of the final mosaic was calculated in relation to the LiDAR-derived control points. 0.27 meters The orthophoto horizontal accuracy is reported as the root-mean-square error (RMSE). Acquisition. Orthophoto data acquisition was conducted from October 1 to October 28, 2013. The survey utilized a UltraCam Eagle 260 megapixel camera system mounted in a Cessna 208-B Grand Caravan. 20131028 Processing. 1. Resolve GPS kinematic corrections for aircraft position data using kinematic aircraft GPS (collected at two hertz) and static ground GPS (one hertz) data collected over geodetic controls. 2. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with attitude data. Sensor heading, position, and attitude will be calculated throughout the survey. 3. Create an exterior orientation (EO) files for each photo image with omega, phi, and kappa. 4. Convert “Level 00” raw imagery into geometrically corrected “Level 02” image files. 5. Apply radiometric adjustments to “Level 02” image files to create “Level 03” Pan-sharpened tiffs. 6. Apply EO to photos, measure ground control points, and perform aerial triangulation. 7. Import DEM, orthorectify, and clip triangulated photos to specified area of interest. 8. Mosaic orthorectified imagery, blending seams between individual photos and correcting for radiometric differences between photos. 20140321 Raster Pixel 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 raster data set represents high resolution orthophotographs acquired during an aerial survey. WSI Sonoma County Agricultural Preservation and Open Space District mailing and physical address

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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. 20140321 WSI physical

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