2021 NOAA NGS Topobathy Lidar DEM: Revillagigedo Channel, Southeast Alaska

NOAA Southeast AK Topobathymetric Lidar data were collected by NV5 Geospatial (NV5) using Leica Hawkeye 4X and Riegl 1560i systems and delivered to NOAA in four blocks. The NOAA Southeast AK Topobathymetric Lidar Block01 was acquired between 20210608 and 20210730 in 13 missions, Block02 was acquired between 20210611 and 20210730 in 14 missions, Block03 was acquired between 20210730 and 20210823 in 6 mission and Block 04 was acquired between 20210625 and 20210823 in 7 missions. The four block dataset includes topobathymetric data in a LAS format 1.4, point data record format 6, with the following classifications in accordance with project specifications and the American Society for Photogrammetry and Remote Sensing (ASPRS) classification standards:

1 - unclassified

2 - ground

7 Withheld -low noise

18 Withheld - high noise

40 - bathymetric bottom or submerged topography

41 - water surface

42 Synthetic- Chiroptera synthetic water surface

43 - submerged feature

45 - water column

64 - Submerged Aquatic Vegetation (SAV)

65 - overlap bathy bottom - temporally different from a separate lift

71 - unclassified associated with areas of overlap bathy bottom/temporal bathymetric differences

72 - ground associated with areas of overlap bathy bottom/temporal bathymetric differences

81 - water surface associated with areas of overlap bathy bottom/temporal bathymetric differences

82 Synthetic - Chiroptera synthetic water surface associated with areas of overlap bathy bottom/temporal bathymetric differences

85 - water column associated with areas of overlap bathy bottom/temporal bathymetric differences

1 Withheld - edge clip

1 Overlap Withheld - unrefracted green data from Chiroptera sensor

The channel bits are as follows:

0 - Riegl VQ1560 NIR channel A and Chiroptera green shallow laser

1 - Riegl VQ1560 NIR channel B and Chiroptera/Hawkeye synthetic water surface

2 - Hawkeye green deep laser

3 - Chiroptera NIR

The user byte is mapped as the following:

0 - Riegl NIR channel A

1 - Riegl NIR channel B

10 - Chiroptera green shallow

11 - Chiroptera green shallow 4X

12 - Chiroptera green shallow synthetic

20 - Hawkeye green deep

21 - Hawkeye green deep 4X

22 - Hawkeye green deep synthetic

30 - Chiroptera NIR

Data in all blocks includes lidar intensity values, number of returns, return number, time, and scan angle. The block01 boundary extent covers 103,002 acres , the Block02 boundary extent covers 76,119 acres, the block03 boundary extent covers 55,929 acres and Block04 boundary extent covers 18,351 acres of the combined topographic and bathymetric project boundaries.

After the initial Southeast AK Topobathymetric Lidar submission, NOAA reviewed the data and provided NV5 Geospatial with a feedback edit review. NV5 Geospatial has corrected these feedback edits and incorporated them into the final block datasets. Additionally, green laser intensity values were normalized for depth for the dataset resulting in a full redelivery of all LAS files. LAS files were compiled in 500 m x 500 m tiles. The final classified lidar data were then transformed from ellipsoid (GRS80) to geoidal height (Geoid12b) and used to create topobathymetric DEMs in GeoTIFF format with 1m pixel resolution.

This lidar data was required by National Oceanic and Atmospheric Administration (NOAA), the National Geodetic Survey (NGS), Remote Sensing Division Coastal Mapping Program (CMP) to enable accurate and consistent measurement of the national shoreline. The CMP works to provide a regularly updated and consistent national shoreline to define America's marine territorial limits and manage coastal resources.

The topobathymetric lidar data includes all lidar returns. An automated grounding classification algorithm was used to determine bare earth and submerged topography point classification. The automated grounding was followed with manual editing. The automated grounding was followed with manual editing. Classes 2 (ground), 40 (submerged topography), 43 (submerged object), and 64 (Submerged aquatic vegetation) were used to create the final DEMs. The full workflow used for this project is documented in the NOAA Finger Lakes Topobathymetric Lidar final report and is available upon request.

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

Work in progress

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.

OS Independent

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 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 (ACCr). The project specification requires horizontal positions to be accurate to 1.0m(RMSE).

Based on a flying altitude of 500 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.008 meters, the RMSEr value for the Leica Chiroptera shallow green and NIR sensor data in all block areas is 0.032 meters, with a ACCr of 0.06 meters at the 95% confidence level.

Block01:The RMSEr value for the Leica Hawkeye deep green sensor data in the block01 area is 0.032 meters, with a ACCr of 0.06 meters at the 95% confidence level based on a flying altitude of 500 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.008 meters. Additionally, based on a flying altitude of 1995 meters, an IMU error of 0.001 decimal degrees, and a GNSS positional error of 0.019 meters, the RMSEr value for the Riegl 1560i NIR sensor data in the block01 area is 0.065 meters, with a ACCr of 0.06 meters at the 95% confidence level.

Block02: The RMSEr value for the Leica Hawkeye deep green sensor data in the block02 area is 0.032 meters, with a ACCr of 0.06 meters at the 95% confidence level based on a flying altitude of 500 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.008 meters. Additionally, based on a flying altitude of 1995 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.019 meters, the RMSEr value for the Riegl 1560i NIR sensor data in the block02 area is 0.126 meters, with a ACCr of 0.06 meters at the 95% confidence level.

Block03: The RMSEr value for the Leica Hawkeye deep green sensor data in the block03 area is 0.032 meters, with a ACCr of 0.06 meters at the 95% confidence level based on a flying altitude of 500 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.008 meters. Additionally, based on a flying altitude of 1995 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.019 meters, the RMSEr value for the Riegl 1560i NIR sensor data in the block03 area is 0.126 meters, with a ACCr of 0.22 meters at the 95% confidence level.

Block04: The RMSEr value for the Leica Hawkeye deep green sensor data in the block4 area is 0.032 meters, with a ACCr of 0.06 meters at the 95% confidence level based on a flying altitude of 500 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.008 meters. Additionally, based on a flying altitude of 1995 meters, an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.019 meters, the RMSEr value for the Riegl 1560i NIR sensor data in the block04 area is 0.126 meters, with a ACCr of 0.22 meters at the 95% confidence level.

Absolute accuracy was assessed using both Non-Vegetated Vertical Accuracy (NVA) and Vegetated Vertical Accuracy (VVA) survey methods. Survey checkpoints were evenly distributed as feasible throughout the project area. NVA compares known ground check point data that were withheld from the calibration and post-processing of the lidar point cloud to the derived gridded bare earth DEM. NVA is a measure of the accuracy of lidar point data in open areas with level slope (less than 20 degrees) where the lidar system has a high probability of measuring the ground surface and is evaluated at the 95% confidence interval (1.96*RMSE). Project specifications require NVA meet 0.196 m accuracy at the 95% confidence interval. Ground check points located in land cover categories other than bare earth or urban were used to compute the Vegetated Vertical Accuracy (VVA). Please refer to the NOAA Southeast AK Topobathymetric Lidar final data report for final accuracies, available upon request.

The block01 area dataset Non-Vegetated Vertical Accuracy tested 0.053 m vertical accuracy at 95% confidence level against the derived bare earth DEM in open terrain using 9 ground check points, based on RMSEz (0.027 m) x 1.9600. The block01 dataset Vegetated Vertical Accuracy tested 0.200 m vertical accuracy at the 95th percentile against the derived bare earth DEM using 3 landclass points.

The Block02 area dataset Non-Vegetated Vertical Accuracy tested 0.045 m vertical accuracy at 95% confidence level against the derived bare earth DEM in open terrain using 16 ground check points, based on RMSEz (0.023 m) x 1.9600. The block02 dataset Vegetated Vertical Accuracy tested 0.160 m vertical accuracy at the 95th percentile against the derived bare earth DEM using 12 landclass points.

The Block03 area dataset Non-Vegetated Vertical Accuracy tested 0.106 m vertical accuracy at 95% confidence level against the derived bare earth DEM in open terrain using 19 ground check points, based on RMSEz (0.054 m) x 1.9600. The block03 dataset Vegetated Vertical Accuracy tested 0.327 m vertical accuracy at the 95th percentile against the derived bare earth DEM using 11 landclass points.

The Block04 area dataset Non-Vegetated Vertical Accuracy tested 0.140 m vertical accuracy at 95% confidence level against the derived bare earth DEM in open terrain using 9 ground check points, based on RMSEz (0.072 m) x 1.9600. The block04 dataset Vegetated Vertical Accuracy tested 0.509 m vertical accuracy at the 95th percentile against the derived bare earth DEM using 4 landclass points.

Data covers the project boundary.

Not applicable

Data is backed up to tape and to cloud storage.