2018 USGS Topobathy Lidar: Gulf Coast Islands (AL, FL, LA)

In October 2018, Quantum Spatial (QSI) was contracted by the United States Geological Survey (USGS) to collect high resolution topobathymetric Light Detection and Ranging (LiDAR) data in the winter of 2018 for the USGS Gulf Coast sites in the Gulf of Mexico. The USGS Gulf Coast project area covers approximately 174 square miles and is comprised of three main areas of interest; Chandeleur Island, Dauphin Island, and the Gulf Islands off the coast of Louisiana, Alabama, and Florida, respectively.

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 2,272 500 m x 500 m tiles.

Geographic Extent: This dataset and derived products encompass an area covering approximately 471 square kilometers of south Florida, Louisiana, and Alabama.

Traditional near-infrared (NIR) LiDAR was fully integrated with green wavelength (bathymetric) LiDAR in order to provide a seamless topobathymetric LiDAR dataset.

Dataset Description: RAW flight line swaths were processed to create 2,272 classified LAS 1.4 files delineated in 500 m x 500 m tiles. Tile naming is based on the easting/northing location of the lower left corner of each tile. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. From the classified point cloud additional derived products include green and NIR intensity images, hydro-flattened breaklines, hydro-flattened DEMs, interpolated topobathymetric DEMs, clipped topobathymetric DEMs, and highest hit surface models of the study area. Ground Control Points were acquired and calibrated by Quantum Spatial, Inc.

Data acquisition was coordinated by Quantum Spatial and all lidar data calibration, and follow-on processing was completed by Quantum Spatial

Ground Conditions: Acquisition below aircraft free of smoke, fog and cloud cover.

NOAA OCM retrieved the processed lidar point cloud from the USGS rockyftp repository and processed it to the Digital Coast.

The purpose of the lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the 3DEP initiative.

The raw lidar point cloud data were used to create classified lidar LAS files, NIR and Green Scanner intensity images, hydro-flattened DEMs, interpolated and clipped topobathymetric DEM's, highest hit surface models, and 3D hydroflattening breaklines of water bodies and lakes within the study area.

USGS Contract No. G16PC00016 CONTRACTOR: Quantum Spatial, Inc.

Ground Control Points were acquired and calibrated by Quantum Spatial, Inc.

Data acquisition was coordinated by Quantum Spatial and all lidar data calibration, and follow-on processing were completed by Quantum Spatial, the prime contractor.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey National Geospatial Program LIDAR Base Specification, Version 1.3",

"ldrsens" : "Riegl VQ880-G",

"ldrmaxnr" : "15",

"ldrnps" : "1.0",

"ldrdens" : "1",

"ldranps" : "0.71",

"ldradens" : "2",

"ldrfltht" : "400",

"ldrfltsp" : "110",

"ldrscana" : "40",

"ldrscanr" : "80 Lines Per Second",

"ldrpulsr" : "550",

"ldrpulsd" : "1.5",

"ldrpulsw" : "0.45",

"ldrwavel" : "532",

"ldrmpia" : "1",

"ldrbmdiv" : "2.0",

"ldrswatw" : "291",

"ldrswato" : "50",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"

},

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey National Geospatial Program LIDAR Base Specification, Version 1.3",

"ldrsens" : "Riegl VQ880-G-IR",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.50",

"ldrdens" : "4",

"ldranps" : "0.35",

"ldradens" : "8",

"ldrfltht" : "400",

"ldrfltsp" : "110",

"ldrscana" : "40",

"ldrscanr" : "80 Lines Per Second",

"ldrpulsr" : "245",

"ldrpulsd" : "3.0",

"ldrpulsw" : "0.90",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.2",

"ldrswatw" : "291",

"ldrswato" : "50",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"

},

"ldraccur" : {

"ldrchacc" : "0.118",

"rawnva" : "0.053",

"rawnvan" : "26",

"clsnva" : "0.046",

"clsnvan" : "26",

"clsvva" : "0.150",

"clsvvan" : "14"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Witheld points (ignore) are identified in these files using the standard LAS Witheld bits.",

"lasolap" : "Swath overage points are identified in these files using the standard LAS Overlap bits",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but Unclassified"

},

"lasclass" : {

"clascode" : "1o",

"clasitem" : "Processed, but Unclassified Overlap Bit"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low Noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "NIR Water Surface"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "20",

"clasitem" : "Ignored Ground"

},

"lasclass" : {

"clascode" : "40",

"clasitem" : "Bathymetric Bottom"

},

"lasclass" : {

"clascode" : "41",

"clasitem" : "Green Scanner Water Surface"

},

"lasclass" : {

"clascode" : "45",

"clasitem" : "Water Column"

}

}}

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 or 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.

LiDAR horizontal accuracy is a function of Global Navigation Satellite System (GNSS) derived positional error, flying altitude, and INS-derived attitude error. The obtained RMSEr value is multiplied by a conversion factor of 1.7308 to yield the horizontal component (ACCr) of the National Standards for Spatial Data Accuracy (NSSDA) reporting standard where a theoretical point will fall within the obtained radius 95 percent of the time. Using a maximum flying height of 400m, this data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 6.8 cm RMSEx / RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 11.8 cm at a 95% confidence level.

The project specifications require that only Non-Vegetated Vertical Accuracy (NVA) be computed for raw lidar point cloud swath files. The required accuracy (ACCz) is: 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSE of 10 cm in the “bare earth” and "urban" land cover classes. The NVA was tested with 67 checkpoints located in bare earth and urban (non-vegetated) areas. These check points were not used in the calibration or post processing of the lidar point cloud data. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. See survey report for additional survey methodologies. Elevations from the unclassified lidar surface were measured for the x,y location of each check point. Elevations interpolated from the lidar surface were then compared to the elevation values of the surveyed control points. AccuracyZ has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.

Specifications for this project also require that bathymetric accuracy meet the standard laid out in the National Coastal Mapping Strategy (NCMS) V1.0 for QL2b Bathy Lidar which was estimated to be 30cm at a 95% confidence level.

Quantitative value: 0.053 0.078, Test that produced the value: Tested 0.053 meters NVA at a 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA). The NVA of the raw lidar point cloud files was calculated against TINs derived from the final calibrated and controlled swath data using 26 independent checkpoints located in Bare Earth and Urban land cover classes with a resulting RMSE of 0.027 meters.

Tested 0.078 meters Topobathymetric Submerged Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA). The topobathymetric submerged vertical accuracy of the classified lidar point cloud files was calculated against against TINs derived from the final calibrated, controlled, and bathymetric classified point data using 66 independent submerged checkpoints with a resulting RMSE of 0.040 meters.

These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. 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 tape and to cloud storage.