Abstract

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, we propose a novel approach for accurate detection and analysis of water wave surface from Airborne LiDAR Bathymetry (ALB) large-scale point clouds data. In our proposed method we 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. We adapted for most types of wave shape anatomies in shallow waters, nearshore, and onshore of the coastal zone. We used a wavelet analysis filter to detect the water wave surface. Then, through the Fourier Transformation Approach, we 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. We 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.

Highlights

  • We illustrate the situations in which the nearshore waves and breaking waves are placed differently: the near-shore waves are placed in the approaching shore-waves and breaking waves are placed in the breaking surf zone

  • We proposed an algorithm for ocean wave detection and wave analysis parameters measurement through the Airborne Light Detection and Ranging (LiDAR) Bathymetry (ALB) point cloud

  • Our experiments show that different types of wave shape anatomies of the ocean surface can be detected and quantified by using ALB system

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Summary

Introduction

Water wave surface monitoring at nearshore plays a key role in facilitating the updating of basic geographic information including geomorphological change, coastal hazards, erosion, and sediment transportation. It aids the management and maintenance of coastal areas. In addition to the function of damaging and warning system, there is a high probability of nearshore infrastructures being damaged in locations with waves. It is crucial to detect the waves before they reach coastal zones. The main challenge of ocean water wave detection is primarily due to the difficulty of acquiring high-quality data especially in the nearshore and breaking surf zone.

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