2022 NOAA NGS Topobathy Lidar DEM of Ofu and Olosega, American Samoa

This data was collected by Woolpert using a Leica HawkEye 4X sensor. The data was acquired from 20221022 - 20221202. The data includes topobathy data in LAS 1.4 format classified as unclassified (1), ground (2), low noise (7), topo water surface (9), high noise (18), bathymetric point (40), bathymetric water surface (41), synthetic derived water surface (42), submerged object (43), International Hydrographic Organization (IHO) S-57 object (44), submerged aquatic vegetation (64), and bathymetric bottom temporal changes (65) in accordance with project specifications. The lidar data in ellipsoid heights was used to create the final topobathymetric DEMs in ellipsoid heights.

Lidar data classes 2, 40 and 43 were used to generate a raster in geotiff format, with 1 meter pixel resolution for the entire area. The raster was then clipped to the tile grid and named according to project specifications to result in tiled 5000m x 5000m topobathymetric DEMs. The project consists of approximately 53 square kilometers of data collected in Ofu-Olesega, American Samoa. This dataset contains 6 5000 m x 5000 m raster tiles.

This data was collected to provide topographic/bathymetric lidar data, digital imagery, and digital shoreline for National Oceanic and Atmospheric Administration (NOAA) nautical charts and other uses.

The full workflow used for this project is found in the final project report submitted to NOAA.

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

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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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

Woolpert performed acquisition and calibration of all lidar data, as well as classification, generation of derivative products, and absolute positional accuracy computation. The DEMs are derived from the source lidar and inherit the accuracy of the source data. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production.

Woolpert performed acquisition and calibration of all lidar data, as well as classification, generation of derivative products, and absolute positional accuracy computation. The DEMs are derived from the source lidar and inherit the accuracy of the source data. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production. The results of the comparison of the topo ground control points with the Ofu Olesega point cloud showed good agreement with an average dZ of 0.001m. The comparison of NVA and FVA check points to the point cloud showed similar results. The NVA points had an RMSE of 0.04m from the point cloud and the FVA at 95th percent confidence level in open terrain using RMSE (z) x 1.9600 was 0.078m.

Not applicable

Data is backed up to tape and to cloud storage.