Bathymetric Extraction Method of Nearshore Based on ICESat-2/ATLAS Data

Abstract:

Water depth is an important topographical parameter that characterizes shallow ocean and coastal environment. Photon-counting light detection and ranging （LiDAR） can penetrate a certain depth of water and provide reliable date support for water depth information extraction. Taking the islands and reefs in the South China Sea as an example， this paper uses the only in-orbit spaceborne photon-counting LiDAR - Ice， Cloud and land Elevation Satellite-2/Advanced Topographic Laser Altimeter System （ICESat-2/ATLAS） to carry out research on depth extraction and accuracy evaluation in shallow water areas of islands and reefs. Firstly， confidence parameter is adopted to remove the coarse noise photons， and the photons in the water surface and bottom are separated according to their density. Secondly， interval estimate and the modified ordering points to identify the clustering structure （OPTICS） are utilized to filter out noise photons in the water surface and bottom respectively， and the modified OPTICS is changed twice by the filter parameters. Then the water surface elevation is obtained by using the random sample consensus （RANSAC） algorithm. Thirdly， the bathymetric information is achieved by the refraction and tide correction. Finally， the airborne bathymetric LiDAR data of South China Sea is used to validate and evaluate the bathymetric accuracy. Compared with the depth results extracted from the high confidence photons and adaptive variable ellipse filtering bathymetric method （AVEBM）， the proposed noise removal algorithm has a higher F value， which is increased by 5.87% and 3.38% respectively. The experimental results indicated that the R² of bathymetric results obtained by ATLAS and airborne LiDAR is 0.91 and root mean square error （RMSE） is 0.53m.