2013 USGS Lidar: Jean Lafitte and Barataria, LA

Digital Aerial Solutions, LLC (DAS) was tasked to collect and process a Light Detection And Ranging (LiDAR) derived elevation dataset for Jean Lafitte and Barataria area located in South of New Orleans, Louisiana. The Jean Lafitte LiDAR survey encompasses 77 square miles and Barataria LiDAR survey encompasses approximately 1408 square miles. Aerial LiDAR data was collected utilizing an ALS60 Sensor. The ALS60 is a discrete return topographic LiDAR mapping system manufactured by Leica Geosystems. LiDAR data collected for the Jean Lafitte survey area has a nominal pulse spacing of 1m and Barataria has a nominal pulse spacing of 2 meters, and includes up to 4 discrete returns per pulse, along with intensity values for each return. The acquisition mission for the Jean Lafitte and Barataria LiDAR survey was coordinated to be acquired in 1 week. Collection began on March 5th 2013 and was completed on March 8th, 2013.

LiDAR datasets were post processed to generate elevation point cloud swaths for each flight line. Deliverables include the point cloud swaths, tiled point clouds classified by land cover type, breaklines to support hydro-flattening of digital elevation models (DEM)s, and bare-earth DEM tiles. Point cloud deliverables are stored in the LAS version 1.2 format, point data record format 1. The tiling scheme for tiled deliverables is a 1500 meter x 1500 meter grid aligned and named according the US National Grid conventions. All deliverables were generated in conformance with the U.S. Geological Survey National Geospatial Program Guidelines and Base Specifications, Version 1.

The NOAA Office for Coastal Management (OCM) downloaded 125 LA_Jean-Lafitte_2013/ laz files and 1791 USGS_LPC_LA_Barataria_2013_LAS_2015/ laz files from this USGS site: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/ and processed the data to the Data Access Viewer (DAV) and https. The two project areas were downloaded and processed at different times.

Hydro breaklines are also available. These data are available for download at the link provided in the URL section of this metadata record. Please note that these products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.

Undetermined

10410

LAS 1.2 format (classes 1,2,7,9,10,15,17,18)

none

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

Data is available for bulk and custom downloads.

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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. These data depict the heights at the time of the survey and are only accurate for that time.

There is not a systematic method of testing when testing horizontal accuracy in LiDAR. However this is tested during calibration of the sensor and is rechecked during the comparing of parallel and perpendicular flight lines. Additionally the horizontal accuracy is checked by collecting building corners during the survey. Lines are then digitized representing the building outline and the differences are measure from each individual survey point to the corner of the building outline. Stats are calculated to ensure horizontal tolerances are met. These measurements resulted in an RMSE of 0.42 meters equals a 0.73 meter horizontal accuracy at the 95 % confidence level. Accuracy defined by NSSDA at the 95 % confidence level would be multiplier by 1.7308 times the RMSE.

Absolute vertical accuracy assessments for the point cloud data are made against ground check point data. For the Jean Lafitte and Barataria surveys, ground check point data consisted of the ground GPS base station and real-time kinematic (RTK) GPS techniques.

Check point locations were collected at 1 - second intervals during the RTK survey. Points collected during the static pre-initialization and post-initialization were removed from the assessment so as not to bias the assessment.

The accuracy assessment was performed using the NSSDA standard method to compute the root mean square error (RMSE) based on a comparison of ground control points (GCP) and filtered LiDAR data points. Filtered LiDAR data has had vegetation and cultural features removed and by analysis represent bare earth elevations. Testing was performed prior to gridding of the filtered LiDAR data points and construction of the 32-bit geotiff format bare earth tiles. The RMSEz figure was used to compute the vertical National Standard for Spatial Data Accuracy (NSSDA). A spatial proximity analysis was used to select edited LiDAR data points contiguous to the relevant GCPs. A search radius decision rule is applied with consideration of terrain complexity, cumulative error and adequate sample size.

Local TIN models of the elevation points are built around each ground check points. The tin model elevation is sampled at the horizontal position of the ground check point. The TIN model elevation and ground check point survey elevation values were used to calculate the fundamental vertical accuracy (FVA) of the swath point clouds as described in NDEP Elevation Guidelines Version 1. The swath FVA of the calibrated LAS TIN tested RMSEz 0.062 meters and 0.122 meters at the 95% confidence level in open terrain.

Ground Truth data was collected of the three major vegetative cover classes and "urban" dispersed within the area of interest. Land cover categories; urban, forested fully grown, brush lands represents less than 10% of the project land cover class in this project so a minimum 20 points in each categories could not be collected; however, a total 110 points were collected in all of the four classes. Points collected in forested and fully grown were collected with a Total Station. Pair of points was surveyed using the Trimble VRS network once completed the total station is used to collect the high vegetation ground class. A Topcon 7000 total station was used to collect all the shots collected in the high vegetation class, due to the limited GPS signal when working in and around tree canopy.

The GPS survey was tied into the Trimble VRS Now Network located in Louisiana. The Trimble VRS Now network is a network of continuously operating GPS reference stations that provides Real Time Kinematic (RTK) capabilities within a Real Time Network (RTN). This allows corrections to be applied to the points as they are being collected, eliminating the need for an adjustment. Several existing control monuments listed in the NSRS database were used as checks within the Trimble VRS Now Network. This confirmed network accuracies were being met during the field survey as well as providing a redundancy check on the Trimble VRSnetwork. The Specified local network accuracy of 5cm at the 95% confidence level was met or exceeded. Data analysis was accomplished by comparing ground truth checkpoints with LIDAR points from the edited data set, which were within 3.3 feet horizontally from the ground truth points. Based on the number of returns and the density of points in this project, it was not necessary to compare to anything further away than 3.3 feet horizontally from the ground truth points. Note that the edited LIDAR points are simply a subset of the raw LIDAR points. The points that fell above the ground surface on vegetation canopies, buildings, or other obstructions were removed from the data set. Comparisons were also made between the survey points and the LIDAR derived terrain surface. These comparisons provide an additional verification of the LIDAR data against the survey data.