2021 USGS Lidar DEM: Western Maryland

Area of collection for MD_Western_1 (Work Unit 223523)

Dates of collection for MD_Western_1 (Work Unit 223523)

Area of collection for MD_Western_2 (Work Unit 300150)

Dates of collection for MD_Western_2 (Work Unit 300150)

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 Zone 17N and 18N, NAD83(2011), meters coordinates and NAVD88 (Geoid18) 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, the point classes and sensors used.

Link to the Fugro lidar report for MD_Western_1

Link to the Fugro lidar report for MD_Western_2

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.

Fugro collected LMS and ALS-derived lidar from December 04, 2021 through December 21, 2021 for the MD_Western_2021_D21 project AOI with 0.71 meters ANPS. Data was collected when environmental conditions meet the criteria specified. To be specific, the following conditions existed prior to launch of the aircraft: 1) Cloud and fog-free between the aircraft and ground, 2) Snow free, 3) No unusual flooding or inundation, and 4) Leaf off. The lidar collection for the MD_Western_2021_D21 Block 1 AOI was accomplished in 09 collections.

Under Fugro's direction, all surveying activities were performed by Fugro's approved ID/IQ subcontractor Terrasurv, Inc. A total of 40 ground control points to support the lidar collection, along with 79 NVA and 61 VVA checkpoints were collected. The National Spatial Reference System (NSRS) was used to provide control for the network. 9 Continuously Operating Reference Stations (CORS) were included in the network. The horizontal datum was the North American Datum of 1983 (NAD83 (2011)), epoch 2010.0. The vertical datum was the North American Vertical Datum of 1988 (NAVD88), realized with GEOID18.

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 low noise points, high 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. Bridge deck points were classified as well during the interactive editing 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). 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 and formatted to LAS v1.4. 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 6 with Adjusted Standard GPS Time at a precision sufficient to allow unique timestamps for each pulse. Correct and properly formatted georeference information as Open Geospatial Consortium (OGC) well known text (WKT) was assigned in all LAS file headers. Each tile has unique File Source ID assigned. The Point Source ID matches to the flight line ID in the flight trajectory files. Intensity values are included for each point, normalized to 16-bit. The following classifications are included: Class 1 - Processed, but unclassified; Class 2 - Bare earth ground; Class 7 - Low Noise; Class 9 - Water; Class 17 - Bridge Decks; Class 18 - High Noise; Class 20 - Ignored Ground (breakline proximity); Class 21 - Snow (if present and identifiable); Class 22 - Temporal exclusion (typically non-favored data in intertidal zones, use as necessary). The classified point cloud data was delivered in tiles without overlap using the project tiling scheme.

The bare earth DEM was generated using the lidar bare earth points and 3D hydro breaklines to a resolution of 0.5 meter. The bare earth points that fell within 1*NPS along the hydro breaklines (points in class 10) were excluded from the DEM generation process. This is analogous to the removal of mass points for the same reason in a traditional photogrammetrically compiled DTM. This process was done in batch using proprietary software. The technicians then used Fugro proprietary software for the production of the lidar-derived hydro flattened bare earth DEM surface in initial grid format at 2 foot GSD. Water bodies (inland ponds and lakes), inland streams and rivers, and island holes were hydro flattened within the DEM. Hydro flattening was applied to all water impoundments, natural or man-made, that are larger than approximately 2 acres in area and to all streams that are nominally wider than 100 feet. This process was done in batch. Once the initial, hydro flattened bare earth DEM was generated, the technicians checked the tiles to ensure that the grid spacing met specifications. The technicians also checked the surface to ensure proper hydro flattening. The entire data set was checked for complete project coverage. Once the data was checked, the tiles were then converted to industry-standard, GIS-compatible, 32-bit floating point raster format. Georeference information is included in the raster files. Void areas (i.e., areas outside the project boundary but within the tiling scheme) are coded using a unique “NODATA” value.

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_Western_2021_D21/MD_Western_1_D21/TIFF/

https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/MD_Western_2021_D21/MD_Western_2_D21/TIFF/