2019 - 2021 NRCS Lidar DEM: MS East

Area 1 dates of collection.

Area 3 dates of collection.

Area 2 dates of collection.

Area 4 dates of collection.

Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base.

Bulk download of data files in GeoTIFF format, based on a horizontal datum/projection of UTM Zones 15 and 16, NAD83(2011), meters (EPSG: 6344 and 6345) and a vertical datum of NAVD88 (GEOID12B) and units in meters (EPSG: 5703). This url links to the USGS copy of the files. These have not been reviewed by OCM and the link is provided here for convenience.

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 USGS work package report that provides project information, vertical accuracy results, classifications used, sensors used, and work unit information.

Link to the additional information available for this data set from the USGS. This information includes reports, tile index shapefiles, and hydro breaklines.

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.

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.

Link to the lidar report for MS_NRCS_East_1

Link to the lidar report for MS_NRCS_East_2 / Northeast collection area.

Link to the lidar report for MS_NRCS_East_3

Link to the lidar report for MS_NRCS_East_4

Link to the lidar report for MS_NRCS_East_2 / Southwest collection area.

Aircraft and Sensor Information and Flight Plan Execution

Atlantic operated a Cessna Caravan (N167PM) outfitted with an Optech Galaxy Prime LiDAR system during the collection of the project area.

Atlantic acquired 65 passes of the AOI as a series of perpendicular and/or adjacent flight-lines executed in 5 flight missions conducted between January 9, 2020 and January 14, 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.

Ground Control Survey

A total of 64 ground survey points were collected in support of this project, including 9 LiDAR Control Points (LCP), 32 Non-vegetated Vertical Accuracy (NVA) and 23 Vegetated Vertical Accuracy (VVA).

Point cloud data accuracy was tested against a Triangulated Irregular Network (TIN) constructed from LiDAR points in clear/open areas. A clear and open area can be characterized with respect to topographic and ground cover variation such that a minimum of 5 times the Nominal Pulse Spacing (NPS) exists with less than 1/3 of the RMSEZ deviation from a low-slope plane. Slopes exceeding 10 percent were avoided.

Each land cover type representing 10 percent or more of the total project area was tested and reported with a VVA. In land cover categories other than dense urban areas, the tested points did not have obstructions 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.

LiDAR Point Cloud Generation

Atlantic used Optech software products to download the IPAS ABGNSS/IMU data and raw laser scan files from the airborne system. Applanix Pospac 8.5 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.

Departures from planarity of first returns within single swaths in non-vegetated areas were assessed at multiple locations with hard surface areas (parking lots or large rooftops) inside the project area. Each area was evaluated using signed difference rasters (maximum elevation – minimum elevation) at a cell size equal to 2 x ANPS, rounded to the next integer.

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.

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).

LiDAR Intensity Imagery LiDAR intensity imagery was created from the final calibrated and classified lidar point cloud. Intensity images were produced from all classified points and posted to a 1.0 meter cell size. Intensity images were cut to match the tile index and its corresponding tile names and delivered in .tif format.

Hydro-line Collection/Conflation Hydro breaklines were compiled using LiDAR intensity data and surface terrain models of the entire project area. After collection, all delineated hydro features were validated for monotonicity and vertical variance. This procedure ensures that no points were floating above ground. Hydro-lines were then encoded into the LiDAR surface and used to hydro-enforce/flatten all significant water bodies. These final hydro-lines were then used in the production of bare Earth digital models to hydro flatten significant water bodies. This product was delivered as an ESRI geodatabase (.gdb) for the entire block area.

Bare-Earth Surface - Digital Elevation Model (DEM) Bare earth Digital Elevation Models (DEMs) were derived using the hydro-lines and bare earth (ground) LiDAR points. All DEMs were created with a grid spacing of 1 meter. DEMs for this project were cut to match the tile index and its corresponding tile names and delivered in 32-bit floating point .tif format.

The NOAA Office for Coastal Management (OCM) created references to the USGS GeoTIFF files that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the raster data as it resides on Amazon Web Services (AWS).

These are the GeoTIFF files that are being accessed:

https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/MS_NRCS_East_2018_B19/MS_NRCS_East_1_2018/TIFF/

https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/MS_NRCS_East_2018_B19/MS_NRCS_East_2_2018/TIFF/

https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/MS_NRCS_East_2018_B19/MS_NRCS_East_3_2018/TIFF/

https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/MS_NRCS_East_2018_B19/MS_NRCS_East_4_2018/TIFF/