Retrieval of directional power spectral density and wave parameters from airborne LiDAR point cloud

Abstract

Increasing magnitude and frequency of extreme events (e.g., floods, waves, storms), along with the demands of shipping (e.g., increasing vessel sizes) and marine engineering (e.g., intensified port development), can compromise operations and result in economic and human loss. Consequently, a re-examining and better understanding of the sea surface topography and, in particular, surface ocean waves is now imperative. Quantifying surface ocean waves’ properties can often be a complex procedure based on the source of measurements and the technique used. For instance, airborne laser scanning (ALS) can provide a high-resolution dataset of 3D spatial sea surface topography with a point cloud density around 6 p/m2 and vertical accuracy of 5–15 cm, from which properties of surface waves can be derived. This study explores a novel method to enhance ALS-derived directional spatial wave spectrum by sampling from the point cloud and adjusting the standard error. As a result, wave parameters such as significant wave height, peak period, wavelength, and dominant wave direction can be obtained. The method was tested in the eastern section of the Baltic Sea. The wave spectra retrieved from ALS were validated with a nearby wave buoy, wave model and an alternative direct geometrical method from a previous study. These comparisons demonstrated good agreement with the significant wave height and peak period having mean differences of 0.10 m and 0.0 s; 0.09 m and 0.2 s; 0.20 m and 0.8 s compared with the buoy, wave model and direct method, respectively. The ALS-detected dominant wave direction varied from 60.0° to 97.0°, whereas the corresponding estimates for the buoy and reginal wave model were 86.5° and 78.9°–83.8°, respectively.