2015-2016 Lake County, California Lidar; Classified Point Cloud

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This graphic displays the footprint for this lidar data set.

Link to data set report.

Link to the quality assurance / quality control report

Source of lidar point cloud downloaded by NOAA

Fugro collected Leica ALS-70 derived lidar over portions of Lake County, California with 0.7 meters ANPS using a twin engine aircraft. The collection was performed using a Leica ALS-70 lidar system, serial number 7108. There are data voids due to snow in the north (client accepted) adn lowered density in fire areas in the south (accepted) due to areas of low near infrared (NIR) reflectivity.

All surveying activities were performed by Fugro. A total of 18 ground control points to support the lidar collection, along with 81 NVA and 63 VVA checkpoints were collected. The static data collected at the RTK base station was downloaded and submitted to the office to be post processed utilizing the NGS Online Positioning User Service (OPUS). The horizontal datum was the North American Datum of 1983 (2011) and the vertical datum was the North American Vertical Datum of 1988 (NAVD 1988), using Geoid 12B.

Fugro was tasked with planning, acquiring, processing, and producing derivative products of LiDAR data collected at a NPS of 0.7 meters, including overlap, for an Area of Interest (AOI) covering a portion of Lake County, California. The AOI covers approximately 1,329 square miles. A 100-meter buffer was added to the AOI covering approximately 1,342 square miles; all products were generated to the limit of this buffered boundary. LiDAR data was acquired using a twin engine aircraft equipped with an antenna and receiver for airborne GPS collection. Flight status was communicated during data collection. All acquired LiDAR data went through a preliminary review to assure that complete coverage was obtained and that there were no gaps between flight lines before the flight crew left the project site. Once back in the office, the data was run through a complete iteration of processing to ensure that it is complete, uncorrupted, and that the entire project area has been covered without gaps between flight lines. There are essentially three steps to this processing: 1) GPS/IMU Processing - Airborne GPS and IMU data was immediately processed using the airport GPS base station data, which was available to the flight crew upon landing the plane. This ensures the integrity of all the mission data. These results were also used to perform the initial LiDAR system calibration test. 2) Raw LiDAR Data Processing - Technicians processed the raw data to LAS format flight lines with full resolution output before performing QC. A starting configuration file is used in this process, which contains the latest calibration parameters for the sensor. The technicians also generated flight line trajectories for each of the flight lines during this process. 3) Verification of Coverage and Data Quality - Technicians checked flight line trajectory files to ensure completeness of acquisition for the flight lines, calibration lines, and cross flight lines. The intensity images were generated for the entire lift at the required 0.7 meter nominal post spacing for the project. The technician visually checked the intensity images against the acquisition boundary to ensure full coverage to the 100 meter buffer beyond the project boundary. The technician also thoroughly reviewed the data for any gaps in project area. The technician generated a sample TIN surface to ensure no anomalies were present in the data. Turbulence was inspected for each flight line; if any adverse quality issues were discovered, the flight line was rejected and re-flown. The technician also evaluated the achieved post spacing against project specified 0.7 meter nominal post spacing as well as making sure no clustering in point distribution.

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 Fugro 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. 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 (Required Accuracy) was met.

Once boresighting was complete for the project, the project was first set up for automatic classification. The LiDAR data was cut to production tiles. The flight line Overlap points, Noise points and Ground points were classified automatically in this process. Fugro utilized commercial software, as well as proprietary, in-house developed software for automatic filtering. The parameters used in the process were customized for each terrain type to obtain optimum results. Once the automated filtering was completed, the files were run through a visual inspection to ensure that the filtering was not too aggressive or not aggressive enough. In cases where the filtering was too aggressive and important terrain were filtered out, the data was either run through a different filter within local area or was corrected during the manual filtering process. Interactive editing was completed in visualization software that provides manual and automatic point classification tools. Fugro utilized commercial and proprietary software for this process. All manually inspected tiles went through a peer review to ensure proper editing and consistency. After the manual editing and peer review, all tiles went through another final automated classification routine. This process ensures only the required classifications are used in the final product (all points classified into any temporary classes during manual editing will be re-classified into the project specified classifications). During this process, the points originally classified as flight line overlap were tagged as withheld points. Once manual inspection, QC and final autofilter is complete for the LiDAR tiles, the LAS data was packaged to the project specified tiling scheme, clipped to project boundary including the 100 meter buffer and formatted to LAS v1.4. It was also re-projected to UTM Zone 10; NAD83(2011), meters; NAVD88(GEOID12B), meters. The file header was formatted to meet the project specification with File Source ID assigned. This Classified Point Cloud product was used for the generation of derived products. This product was delivered in fully compliant LAS v1.4, Point Record Format 1 with Adjusted Standard GPS Time at a precision sufficient to allow unique timestamps for each return. Georeference information is included in all LAS file headers. Intensity values are included for each point. Each tile has unique File Source ID assigned. The Point Source ID matches to the flight line ID in flight trajectory files. The following classifications are included: Code 1 – Processed, but unclassified; Code 2 – Bare-earth ground; Code 7 – Noise (low or high, manually identified, if needed); Code 9 – Water; and Code 10 – Ignored Ground (Breakline Proximity); Code 17 - Bridges; Code 18 - High noise.

NOAA downloaded the lidar point cloud from USGS in NAD82(2011) UTM zone 11 meters with vertical coordinates in meters NAVD88 (Geoid12b). Data were converted to geographic coordinates and ellipsoid heights for ingest in the NOAA Digital Coast Data Access Viewer.