基于ICESat-2/ATLAS数据的近海岸水深提取

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

摘要:

水深是表征海洋浅水和海岸环境的重要地形要素，光子计数激光雷达可穿透一定深度的水体，为水深信息提取提供可靠的数据支持。以我国南海岛礁为例，利用目前唯一在轨的星载光子计数激光雷达-ICESat-2/ATLAS数据开展岛礁浅水水深提取及精度评价研究。首先根据置信度参数对原始光子数据进行粗去噪，基于点密度分布差异分离水面和水底光子；然后对水面光子采用区间估计方法精去噪，利用RANSAC算法拟合水面高程；通过改进滤波参数，基于改进OPTICS算法对水底光子进行两次聚类，实现水底光子的精去噪，进而通过折射校正和潮汐校正提取近岸水深；最后利用机载LiDAR测深数据进行验证。实验结果表明，与ATL03高置信度光子数据和AVEBM去噪结果相比，该精去噪算法具有更高的F值，分别提高了约5.87％和3.38％；水深提取结果与机载测深数据的R²为0.91，均方根误差RMSE为0.53m。

关键词:ICESat-2/ATLAS;光子去噪;激光测深;区间估计;改进OPTICS;近岸水深

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.

Key words:ICESat-2/ATLAS;photon noise removal;laser depth sounding;interval estimate;the modified ordering points to identify the clustering structure (OPTICS);nearshore bathymetry