Data Management Plan (Deprecated)

USGS NGTOC task order G17PD00242 required Spring 2017 LiDAR surveys to be collected over 7,931 square miles covering part or all of 22 counties in SW Georgia. These counties are Baker, Bleckley, Crawford, Crisp, Decatur, Dodge, Dooly, Early, Houston, Macon, Meriwether, Miller, Muscogee, Peach, Pulaski, Seminole, Telfair, Terrell, Troup, Turner, Twiggs, and Wilcox. Aerial LiDAR data for this task order was planned, acquired, processed, and produced at an aggregate nominal pulse spacing (ANPS) of 0.7 meters and in compliance with USGS National Geospatial Program LiDAR Base Specification version 1.2.

Isolated gaps in GPS data were identified in several missions covering this project. As both, the IMU data and pulse data, were present across these gaps, using the fixed positions of the GPS on either end, the aircraft velocity across the gaps, and the IMU data, LiDAR calibration staff were able to reach an effective solution to address the GPS voids. Because these gaps were not uniform in size or correction, this extended the iterative LiDAR calibration efforts on this project. Subsequent rigorous data checking confirmed adequate results to meet the required accuracy specs. The USGS QA Team reviewed affected data (blocks) for this project and found no QA/QC discrepancies to report regarding those gaps.

In three missions 123_20190317_1, 123_20190318_1, and 123_20190318_2 there were symptoms of skunk striping present in the collected data. These artifacts are manifested by low noise points at nadir and are believed to have been caused by exhaust from the aircraft during collection. Atlantic isolated the points affected by channel and by intensity, and classed them out to noise and flagged them as withheld. We were able to maintain the integrity of the surface and still meet density requirements to meet spec.

This metadata supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.

Lineage Statement:
The Southwest GA 22 County lidar was ingested into the Data Access Viewer for custom product generation by leveraging USGS hosted Entwine Point Tiles.

Process Steps:

• 2017-11-24 00:00:00 - Aircraft and Sensor Information and Flight Plan Execution: Blocks B1a, B1b, B2: Atlantic operated a Cessna (N732JE) outfitted with a Leica ALS70-HP LiDAR system during the collection of the project area. Atlantic acquired 220 passes of the AOI as a series of perpendicular and/or adjacent flight-lines executed in 32 flight missions conducted between March 15, 2017 and November 24, 2017. Onboard differential Global Navigation Satellite System (GNSS) unit(s) recorded sample aircraft positions at 2 hertz (Hz) or more frequency. LiDAR data was only acquired when a minimum of six (6) satellites were in view. Twenty-three (23) Continuously Operating Reference Stations (CORS) were used to control the LiDAR acquisition for the defined project area. Block 5: Atlantic operated a Caravan (N167PM) outfitted with an Optech Galaxy T2000 LiDAR system during the collection of the project area. Atlantic acquired 85 passes of the AOI as a series of perpendicular and/or adjacent flight-lines executed in 7 flight missions conducted between January 19, 2021 and January 30, 2021. Onboard differential Global Navigation Satellite System (GNSS) unit(s) recorded sample aircraft positions at 2 hertz (Hz) or more frequency. LiDAR data was only acquired when a minimum of six (6) satellites were in view. Sixteen (16) Continuously Operating Reference Stations (CORS) were used to control the LiDAR acquisition for the defined project area.
• 2017-04-30 00:00:00 - Ground Control Survey: Blocks B1a, B1b, B2: A total of 156 ground survey points were collected in support of this project, including 32 LiDAR Control Points (LCP), 73 Non-vegetated Vertical Accuracy (NVA) and 51 Vegetated Vertical Accuracy (VVA) points. Point cloud data accuracy was tested against a Triangulated Irregular Network (TIN) constructed from LiDAR points in clear and open areas. A clear and open area can be characterized with respect to topographic and ground cover variation such that a minimum of five (5) times the Nominal Pulse Spacing (NPS) exists with less than 1/3 of the RMSEZ deviation from a low-slope plane. Slopes that exceed ten (10) percent were avoided. Each land cover type representing ten (10) percent or more of the total project area were tested and reported with a VVA. In land cover categories other than dense urban areas, the tested points did not have obstructions forty-five (45) degrees above the horizon to ensure a satisfactory TIN surface. The VVA value is provided as a target. It is understood that in areas of dense vegetation, swamps, or extremely difficult terrain, this value may be exceeded. The NVA value is a requirement that must be met, regardless of any allowed “busts” in the VVA(s) for individual land cover types within the project. Checkpoints for each assessment (NVA and VVA) are required to be well-distributed throughout the land cover type, for the entire project area. Block 5: A total of 39 ground survey points were collected in support of this project, including 8 LiDAR Control Points (LCP), 17 Non-vegetated Vertical Accuracy (NVA) and 14 Vegetated Vertical Accuracy (VVA).Point cloud data accuracy was tested against a Triangulated Irregular Network (TIN) constructed from LiDAR points in clear and open areas. A clear and open area can be characterized with respect to topographic and ground cover variation such that a minimum of five (5) times the Nominal Pulse Spacing (NPS) exists with less than 1/3 of the RMSEZ deviation from a low-slope plane. Slopes that exceed ten (10) percent were avoided. Each land cover type representing ten (10) percent or more of the total project area were tested and reported with a VVA. In land cover categories other than dense urban areas, the tested points did not have obstructions forty-five (45) degrees above the horizon to ensure a satisfactory TIN surface. The VVA value is provided as a target. It is understood that in areas of dense vegetation, swamps, or extremely difficult terrain, this value may be exceeded. The NVA value is a requirement that must be met, regardless of any allowed “busts” in the VVA(s) for individual land cover types within the project. Checkpoints for each assessment (NVA and VVA) are required to be well-distributed throughout the land cover type, for the entire project area.
• 2019-04-18 00:00:00 - LiDAR Point Cloud Generation: Atlantic used Leica software products to download the IPAS ABGNSS/IMU data and raw laser scan files from the airborne system. Waypoint Inertial Explorer is used to extract the raw IPAS ABGNSS/IMU data, which is further processed in combination with controlled base stations to provide the final Smoothed Best Estimate Trajectory (SBET) for each mission. The SBETs are combined with the raw laser scan files to export the LiDAR ASCII Standard (*.las) formatted swath point clouds.
• 2019-04-18 00:00:00 - LiDAR Calibration: Using a combination of GeoCue, TerraScan and TerraMatch; overlapping swath point clouds are corrected for any orientation or linear deviations to obtain the best fit swath-to-swath calibration. Relative calibration was evaluated using advanced plane-matching analysis and parameter corrections derived. This process was repeated interactively until residual errors between overlapping swaths, across all project missions, was reduced to ≤2cm. A final analysis of the calibrated lidar is preformed using a TerraMatch tie line report for an overall statistical model of the project area. Individual control point assessments for this project can be found in Section VI of this report. Upon completion of the data calibration, a complete set of elevation difference intensity rasters (dZ Orthos) are produced. A user-defined color ramp is applied depicting the offsets between overlapping swaths based on project specifications. The dZ orthos provide an opportunity to review the data calibration in a qualitative manner. Atlantic assigns green to all offset values that fall below the required RMSDz requirement of the project. A yellow color is assigned for offsets that fall between the RMSDz value and 1.5x of that value. Finally, red values are assigned to all values that fall beyond 1.5x of the RMSDz requirements of the project.
• 2019-04-18 00:00:00 - LiDAR Classification: Multiple automated filtering routines are applied to the calibrated LiDAR point cloud identifying and extracting bare-earth and above ground features. GeoCue, TerraScan, and TerraModeler software was used for the initial batch processing, visual inspection and any manual editing of the LiDAR point clouds. Atlantic utilized collected breakline data to preform classification for class 9 (Water).
• Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 Web Mercator (EPSG 3857). Vertically, the data were converted to meters and no changes were made to the vertical datum (NAVD88 GEOID12B; EPSG 5703).
• 2022-02-14 00:00:00 - References to the entwine point tiles and data reports were ingested into the Digital Coast Data Access Viewer. No changes to the data were made at this point. The Data Access Viewer will access the point cloud as it resides on AWS under the usgs-lidar-public container.

Data is available online for bulk and custom downloads.

Data is backed up to tape and to cloud storage.