2018 La DOTD Lidar DEM: Amite Watershed (LA, MS)

Original Product: These are Digital Elevation Model (DEM) data for the Amite Watershed Louisiana, as part of the required deliverables for the Louisiana Department of Transportation and Development Amite Watershed, Lidar Project. Class 2 (ground) lidar points in conjunction with the hydro breaklines were used to create a 0.6 meter hydro-flattened Raster DEM.

Original Geographic Extent: The Amite Watershed, including East Feliciana, St. Helena, East Baton Rouge, Livingston, Iberville, and Ascension Parishes, Louisiana, and Amite, Wilkinson, Franklin, and Lincoln Counties, Mississippi, covering approximately 1,884 square miles.

Original Dataset Description: The Louisiana Department of Transportation and Development Amite Watershed, 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 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), Universal Transverse Mercator, meters and vertical datum of NAVD88 (GEOID12B), meters. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 2410 individual 1500 m x 1500 m tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 1500 m x 1500 m schema.

Ground Conditions: Lidar was collected in early 2018, while no snow was on the ground and rivers were at slightly higher than normal levels causing flooding in areas along the Mississippi river. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Forte and Tablada established a total of 75 ground control points that were used to calibrate the lidar to known ground locations established throughout the Amite Watershed project area. An additional 125 independent accuracy checkpoints, 71 in Bare Earth and Urban landcovers (71 NVA points), 54 in Tall Grass and Brushland/Low Trees categories (54 VVA points), 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 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, Breaklines and Raster DEM. The purpose of these lidar data was to produce high accuracy 3D hydro-flattened Digital Elevation Model (DEM) with a 0.6 meter cell size. These lidar point cloud data were used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

Raster File Type = ESRI Grid Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 0.6 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 Louisiana Dept. of Transportation & Development, USGS, 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.

Not tested

The same 131 checkpoints that were used to test the vertical accuracy of the lidar were used to validate the vertical accuracy of the final DEM products as well. Accuracy results may vary between the source lidar and final DEM deliverable. DEMs are created by averaging several lidar points within each pixel which may result in slightly different elevation values at each survey checkpoint when compared to the source LAS, which does not average several lidar points together but may interpolate (linearly) between two or three points to derive an elevation value. The vertical accuracy of the DEM is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations. Dewberry typically uses LP360 software to test the swath lidar vertical accuracy, Terrascan software to test the classified lidar vertical accuracy, and Esri ArcMap to test the DEM vertical accuracy so that three different software programs are used to validate the vertical accuracy for each project. Out of the 131 checkpoints received from the surveyor, there were six checkpoints that were removed from vertical accuracy testing because they fell outside the project boundary, and one checkpoint that was removed because no data was sent with it.

This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =6.8 cm, equating to +/- 10 cm at 95% confidence level. Actual VVA accuracy was found to be +/- 10.8 cm at the 95th percentile.

Datasets contain complete coverage of tiles. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. There is a known void 274427.58 sq m (0.1 sq mi) in size in tiles 15RXP7252 and 15RXP7254. Please see the project report for more details and explanation of cause for this void. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.

With the exception of the small void mentioned in the Completeness tag, data covers the entire area specified for this project.

Data is backed up to tape and 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.