2021 USGS Topobathy Lidar DEM: Potomac River, MD

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, UTM 18N NAD83(2011) coordinates and in orthometric (NAVD88, Geoid 18) 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 Dewberry lidar report.

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

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

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

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.

The boresight for each lift was done individually as the solution may change slightly from lift to lift. The initial points for each mission calibration were inspected for flight line errors, flight line overlap, slivers or gaps in the data, point data minimums, or issues with the lidar unit or GPS. Roll, pitch and scanner scale were optimized during the calibration process until the relative accuracy was met.

Dewberry utilized Bayesmap StripAlign for this alignment procedure. This alignment procedure corrected systematic issues globally, per aircraft lift, per flightline, and finally based on local errors along the flight trajectory. Error adjustments included internal sensor parameters. Due to the complex geometric relationship of the elliptical scan pattern the forward and reverse directions must be aligned independently. Additionally, since the green and NIR scanner map different surfaces, they were also aligned independently, then corrected to match each other.

Difference rasters (DZ orthos) were generated, adjustment parameters were reviewed, and registration/match regions were reviewed to ensure data quality.

A final vertical accuracy check of the boresighted flight lines was completed against the surveyed check points after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level was met.

Point classification was performed according to USGS Lidar Base Specification 2.1. Bare earth DEMs were exported from the classified point cloud. Synthetic points generated by CZMIL refraciton correction algorithms are present in this dataset. Please see the final project report for more details on the synthetic points

Dewberry used algoritms in TerraScan to create the intial ground/submerged topography surface.

Dewberry used rasterized aggregate extents of refracted points to create automated 2-D breaklines with LAStools and ArcGIS. Light travels at different speeds in air versus water and its speed and direction of travel change when it enters the water column. The refraction correction process accounts for this difference by adjusting the depth (distance traveled) and horizontal position (change of angle/direction) of the lidar points acquired within water. These breaklines delineate areas where the refraction correction was applied to the lidar data by CZMIL's automated refraction correction software based on the software's detection of water. The class 42 synthetic surface is generated by the software as a reference surface from which to perform the correction.

Dewberry used the 2-D refraction extents and additional bathy features to classify the bathymetric bottom and ground points properly in TerraScan.

Geometrically unused points at the edges of flight lines were flagged using the withheld bit. This includes synthetically generated class 42 (synthetic water surface) points at the edges of flight lines. All class 42 points were flagged using the synthetic bit. The withheld bit was set on class 7 and class 18 in TerraScan after all classification was complete.

All lidar data was peer-reviewed. Dewberry's QAQC also included creating void polygons for use during review. All necessary edits were applied to the dataset. LASTools software was used to update LAS header information, including all projection and coordinate reference system information. The final lidar data are in LAS format 1.4 and point data record format 6.

All data was then verified by an Independent QC department within Dewberry. The independent QC was performed by separate analysts who did not perform manual classification or editing. The independent QC involved quantitative and qualitative reviews.

Digital elevation models were created using only ground (2) and submerged topography (40) lidar point data. A triangulated irregular network (TIN) was generated from these data and rasterized at a 1 m spatial resolution using the LAStools 'blast2dem' utility. Void polygons delineating areas of extremely sparse or non-existent bathymetric coverage were used in ArcGIS to clip large areas of interpolation in the DEM. The void polygon creation process is described in the void polygon metadata and final project report. Both tiled and merged DEMs are delivered for this project.

DEMs were reviewed using Global Mapper and ArcGIS to check for surface anomalies, incorrect elevations, and unacceptable voids in the data.

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/MD_PotomacP2_Tobobathy_2021_D21/MD_PotomacP2_TB_2021/TIFF/