2018 - 2019 NRCS Lidar: Catahoula Concordia, LA

LA_Catahoula_Concordia_1 (D1, Work Unit 74197)

Dec 2 - 15, 2019

LA_Catahoula_Concordia_2 (D2, Work Unit 208932)

Jan 24, 2018 - Dec 15, 2019

LA_Catahoula_Concordia_3 (D3, Work Unit 211679)

Oct 6 - Nov 21, 2019

Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.

Bulk download of data files in LAZ format, UTM Zone 15N NAD83(2011) meters coordinates and NAVD88 (Geoid12B) elevations in meters.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

Link to the reports, breaklines, metadata, and spatial metadata.

Link to the USGS Project Report that provides information about the project, vertical accuracy results, and the point classes and sensors used.

Link to the lidar report

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer.

Aerial LiDAR Acquisition: LiDAR acquisition was done using Hardy-Anders Field Nachez Admas County Airport(KHEZ) as the base airports. DAS used two dedicated GPS base station located at the respected airports to support the aerial LiDAR acquisition. DAS used Leica's Terrian Mapper LiDAR Sensor (SN90524) for the acquisition.

LiDAR Data Processing: Inertial Explorer 8.9 software was used to compute inertial solution file (*.sol) for each mission using ground GPS base station. The resulting solution was checked to ensure a minimum accuracy of +/- 0.05m, combined separation, for horizontal and vertical positions. Inertial Explorer methodology integrates Inertial Navigation Solution by processing the GPS data and Inertial Measurement Unit (IMU). The software applies the reference lever arms for the GPS and IMU during the process to determine the trajectory (position and orientation) of the LiDAR sensor during the acquisition mission. Inertial Explorer generated graphical results was reviewed to ensure that the IMU data was healthy. These results are found in Appendix D.

Raw LiDAR sensor ranging data and the final solution sensor trajectory (*.sol), from Inertial Explorer, were processed in Leica’s Cloud Pro software to produce LiDAR point cloud swath for each flight line in LAS version 1.4 file format. Quality control of the swath point cloud was performed to validate proper functioning of the sensor system, full coverage of the project area and point density of the LiDAR data. Swath point clouds were assigned unique file source identification. The data was found to be complete and consistent with the sensor calibration parameters.

LiDAR Calibration:HxMap is the common workflow platform for Leica airborne sensors. The processing workflow involves; Ingest, Block Creation, LiDAR Matching, Quality Assurance (QA) and Product Generation.

LiDAR is processed in HxMap by generating point clouds from raw sensor data during the Ingest step. Noise filtering, sensor installation calibration and atmospheric condition parameters are also applied during the ingest process. Once all data is processed through ingest, they are assembled into a block for LiDAR Matching. The LiDAR Matching step resolves LiDAR registration errors which remain in the point clouds after sensor and installation calibration parameters are applied in the ingest step. QA tool is run on the Block after LiDAR Matching to verify quality of results. QA results are reviewed to ensure that, 95% of patches less thand 5cm for Vertical Scan Direction and Vertical Line Separation. Ground control points are also included to assess absolute accuracy for the point cloud data. LiDAR products are finally generated in the Product Generation step as LAS swaths (LAS 1.4). Vertical (Z) shift (calculated from QA step) is also applied during the product generation.

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) and no changes were made to the vertical (NAVD88 GEOID12B meters).

The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tiles (EPT) that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container.

These are the AWS URLs being accessed:

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/LA_Catahoula_Concordia_1_2017/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/LA_Catahoula_Concordia_2_2017/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/LA_Catahoula_Concordia_3_2017/ept.json