Quantum Spatial, Inc. 20191106 raster data Product: QL2 Intensity Image Geographic Extent: This dataset and derived products encompass an area covering approximately 463 square miles on the North Slope of Alaska. Dataset Description: The North Slope Borough 3DEP LiDAR project called for the planning, acquisition, and processing of LiDAR data collected at an aggregate nominal pulse spacing (ANPS) of either 0.35 meters or 0.71 meters depending on area. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data was developed based on the NAD83(2011) horizontal datum and NAVD88 (GEOID12B) vertical datum. Data was projected in the appropriate Alaska State Plane Zone for its location. The delivery areas are located in AKSP Zones 2,4,6,7, and 8. All units are in US Survey Feet. The 2018 delivery areas encompasses the Nuiqsut, Kaktovik, Wainwright, Atqasuk, Barrow, Barrow Village, Barrow South, and Deadhorse areas of interest. The 2019 delivery encompass the Anaktuvuk Pass, Point Lay, and Point Hope areas of interest. LiDAR data was delivered as processed Classified LAS 1.4 files, formatted to 6,494 individual 1500 ft x 1500 ft tiles. Derived products include: tiled Intensity Imagery, tiled DZ orthos, tiled and mosaicked bare earth DEMs and shaded relief rasters, tiled and mosaicked Highest Hit Digital Surface Models and shaded relief rasters, tiled 2 ft contour shapefiles, 3D building footprints, and 3D waters edge breaklines. Ground Conditions: LiDAR was collected in summer 2018 and 2019, while the presence of snow on the ground was at a minimum and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Umiaq established a total of 42 ground control points distributed throughout the North Slope Borough 3DEP, Alaska project area. LiDAR data was calibrated to these known ground locations. An additional 88 independent accuracy checkpoints, 56 in Bare Earth and Urban landcovers (NVA points) and 32 in Tall Grass, Tundra and Shrubbery categories (VVA points), were used to assess the vertical accuracy of the project data. These checkpoints were not used to calibrate or post process the data. The purpose of the lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the 3DEP initiative. The raw lidar point cloud data were used to create classified lidar las files, hydroflattened DEMs, highest hit DSMs, intensity images, DZ orthos, 2 foot contours, 3D hydro breaklines, and 3D building footprints. CONTRACTOR: Quantum Spatial, Inc. Ground Control Points were acquired by Umiaq. Quantum Spatial coordinated the data acquisition and performed all calibration, follow up processing, and creation of the final derived products. Raster File Type = TIFF Bit Depth/Pixel Type = 8 bit Raster Cell Size = 3.0 ft (QL2) Intensity Values Normalized To = 16 bit 20180714 20190818 ground condition: Acquisition below aircraft free of smoke, fog and cloud cover In Work None planned -152.050676 -148.254526 70.314483 68.090958 1387299.058915 1855838.898815 5964449.713587 5154556.577098 None Intensity Images Lidar None Alaska Anaktuvuk Pass, Nuiqsut, Deadhorse North Slope No restrictions apply to these data. 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. Acknowledgement of the U.S. Geological Survey would be appreciated for products derived from these data. Data covers the entire area specified for the contracted area. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. LiDAR Pre-Processing: 1. Review flight lines and data to ensure complete coverage of the study area and positional accuracy of the laser points. 2. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. 3. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with sensor head position and attitude recorded throughout the survey. 4. Calculate laser point position by associating SBET position to each laser point return time, scan angle, intensity, etc. Create raw laser point cloud data for the entire survey in *.las format. Convert data to orthometric elevations by applying a geoid correction. 5. Import raw laser points into manageable blocks to perform manual relative accuracy calibration and filter erroneous points. Classify ground points for individual flight lines. 6. Using ground classified points per each flight line, test the relative accuracy. Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calculate calibrations on ground classified points from paired flight lines and apply results to all points in a flight line. Use every flight line for relative accuracy calibration. 7. Adjust the point cloud by comparing ground classified points to supplemental ground control points. 9. Points were output as TIFFS colored by intensity values (0-255). 20191101 Raster Pixel 500 500 State Plane Coordinate System 1983 5004 0.99990000 -150.0 54.0 1640416.66666667 0.0 coordinate pair 3.0 3.0 US Survey Feet North American Datum of 1983 (2011) Geodetic Reference System 80 6378137.0 298.257222101 20191106 20191106 Quantum Spatial, Inc. mailing and physical

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