Airborne Scanning

Sajjad Roshandel et al.: 3D Ocean Water Wave Surface Analysis on Airborne LiDAR Bathymetric Point Clouds 30.09.2021

Water wave monitoring is a vital issue for coastal research and plays a key role in geomorphological changes, erosion and sediment transportation, coastal hazards, risk assessment, and decision making. However, despite missing data and the difficulty of capturing the data of nearshore fieldwork, the analysis of water wave surface parameters is still able to be discussed. In this paper, the authors propose a novel approach for accurate detection and analysis of water wave surface from Airborne LiDAR Bathymetry (ALB) large-scale point clouds data. In their proposed method they combined the modified Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering method with a connectivity constraint and a multi-level analysis of ocean water surface. They adapted for most types of wave shape anatomies in shallow waters, nearshore, and onshore of the coastal zone. They used a wavelet analysis filter to detect the water wave surface. Then, through the Fourier Transformation Approach, they estimated the parameters of wave height, wavelength, and wave orientation. The comparison between the LiDAR measure estimation technique and available buoy data was then presented. The authors quantified the performance of the algorithm by measuring the precision and recall for the waves identification without evaluating the degree of over-segmentation. The proposed method achieves 87% accuracy of wave identification in the shallow water of coastal zones.

The full article was published in the Remote Sensing Journal (2021, 13(19), 3918), publishing house: MDPI, and can be found here.