2022 NOAA NGS Topobathy Lidar Post Hurricane Ida: Louisiana

This data was collected by Woolpert using a Leica Chiroptera 4X sensor. The data was acquired between 20221004 to 20221021. The data includes topobathy data in an LAS 1.4 format file 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. This data set also includes lidar intensity values.

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.

Data include all lidar returns. Outliers or false returns (e.g., returns from birds, atmospheric particles, and/or system noise) may be present in the data. An automated ground classification algorithm was used to determine bare earth point classification. It should be noted that not all returns were correctly classified; therefore the user should examine for acceptability.

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.

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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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

OS Independent

The data positions were obtained using post processed methods. The horizontal accuracy of the data is better than plus or minus 1.0 m at 1 sigma.

Woolpert performed acquisition and calibration of all lidar data, as well as classification, generation of derivative products, and absolute positional accuracy computation. The data positions were obtained using post processed methods. Data used to test the lidar was collected with Static GPS Observations and compared against the published data. Woolpert collected check points across the project area. The results of the comparison of the topo ground control points with the Louisiana shoreline point cloud showed good agreement with an average dZ of -0.016m. The comparison of NVA and FVA check points to the point cloud showed similar results. The NVA points had an RMSE of 0.041m (1 sigma) from the point cloud and the FVA at 95th percent confidence level in open terrain using RMSE (z) x 1.9600 was 0.080m.

Not applicable

Data is backed up to tape and to cloud storage.