2022 USGS Topobathy Lidar DEM: Breton Island, LA

Original Dataset Product: These are Digital Elevation Model (DEM) data delivered as part of the Louisiana Breton topobathy lidar project. Class 2 (ground) and class 40 (bathymetry) lidar points were used to create a 0.5-meter merged topo-bathy DEM.

Original Dataset Geographic Extent: Breton, Louisiana, covering approximately 129.4 square miles.

Original Dataset Description: The Louisiana Breton Topobathymetric Lidar project called for the planning, acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters (QL1) for topographic areas and 0.71 meter (QL2b) for bathymetric areas. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, 2024 rev A. The data was developed based on a horizontal projection/datum of NAD83 (2011), UTM zone 16N, meters and vertical datum of NAVD88 (Geoid 18), meters. Lidar data were delivered as processed Classified LAS 1.4 files, formatted to 1570 individual 500 m x 500 m tiles, as tiled Intensity Imagery, and as tiled topobathymetric DEMs; all tiled to the same 500 m x 500 m schema.

Original Dataset Ground Conditions: Lidar was collected from October 6, 2022 to November 3, 2022, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Dewberry established 17 ground control points (GCP) and 5 bathymetric control points (BCP) that were used to calibrate the lidar to known ground positions established throughout the project area. An additional 27 independent accuracy checkpoints--20 in bare earth and urban land cover (NVA), 7 in submerged topography land cover (BVA)--were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post-process the data.

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

To acquire detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments and elevation modeling, etc. Classified LAS files are used to show the manually reviewed bare earth surface. This allows the user to create Intensity Images, Refraction Extents and Raster DEM. The purpose of these lidar data was to produce high accuracy 3D hydro-flattened Digital Elevation Model (DEM) with a 0.5 meter cell size. These lidar point cloud data were used to create intensity images, Refraction Extents, and topobathymetric DEMs as necessary.

Raster File Type = GeoTiff Bit Depth/Pixel Type = 32 bit float Raster Cell Size = 0.5 Meter Interpolation or Resampling Technique = Triangulated Irregular Network Required Vertical Accuracy = 19.6 cm NVA

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners.

Data is available online for bulk and custom downloads.

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations.

CZMIL SuperNOVA; CARIS; LAStools; Microstation; Terrascan; ArcGIS 10.6; Microsoft Windows 10 Enterprise Service Pack 1

Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the lidar. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the lidar. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the lidar cannot always be tested.

Lidar vendors calibrate their lidar systems during installation of the system and then again for every project acquired. Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions. This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 41 cm RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 1 meter at a 95% confidence level.

Horizontal accuracy testing requires well-defined checkpoints that can be visually identified in the dataset. Elevation datasets, including lidar datasets, do not always contain well-defined checkpoints suitable for horizontal accuracy assessment. Dewberry reviewed all NVA checkpoints to determine which, if any, of these checkpoints were located on photo-identifiable features in the intensity imagery. This subset of checkpoints was used for horizontal accuracy testing.

The horizontal accuracy testing steps used by Dewberry are summarized as follows:

1. Dewberry's team surveyed X, Y, and Z coordinates for discrete checkpoints in accordance with project specifications. Dewberry targeted half of the NVA checkpoints for location on features that would photo-identifiable in the intensity imagery.

2. Following initial processing, Dewberry located the photo-identifiable features in the intensity imagery.

3. Dewberry computed the differences in X and Y values between the surveyed coordinates and the lidar coordinates of the photo-identifiable feature.

4. Horizontal accuracy was assessed based on these data using NSSDA methodology where horizontal accuracy is calculated at the 95% confidence level.

USGS DEM Determined Vertical Accuracy

Non-Vegetated Vertical Accuracy (NVA) = 9.68 cm RMSE

Bathymetric Vertical Accuracy (BVA) = 21.69 cm at the 95th Percentile

Topobathymetric data covers the project boundary to the fullest extent possible depending on water clarity, environmental conditions, and sensor signal returns. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.

Data covers the entire area specified for this project.

Data is backed up to cloud storage.

The NOAA Office for Coastal Management (OCM) ingested references to the USGS GeoTIFF files that are hosted on Amazon Web Services (AWS), into the Digital Coast Data Access Viewer (DAV). The DAV accesses the raster data as it resides on AWS.