To derive shallow water bathymetry for coastal areas, a common approach is to deploy a scanning airborne bathymetric light detection and ranging (LiDAR) system or a shipborne echosounder for ground surveys. However, recent advancements in satellite remote sensing, including the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) offer new tools for generating satellite derived bathymetry (SDB). The key payload onboard ICESat-2 is the Advanced Topographic Laser Altimeter System (ATLAS), a micro-pulse, photon-counting LiDAR system, simultaneously emitting six separate 532 nm beams at 10 kHz pulse rate. However, despite its high resolution, the major limitation for bathymetry is that ICESat-2 only provides along-track height profiles, leaving observation gaps between the parallel ground tracks. Merging ICESat-2 observations with optical multispectral imagery, as demonstrated herein, provides an effective solution for deriving a full scene of water depth in light of the spectral attenuation behavior.

This study aims to combine ICESat-2 and Sentinel-2 optical data to derive shallow water bathymetry (depth <20 m) at six islands and reefs in the South China Sea. ICESat-2 ATL03 point clouds of georeferenced photons are first filtered to determine the seafloor elevation along the ground track. Results indicate a root-mean-square error (RMSE) of 0.26–0.61 m as compared with independent observations from an airborne LiDAR campaign. Next, three semi-empirical functions, namely the Modified Linear/Polynomial/Exponential Ratio Models with its kernel formed by the log ratio between Sentinel-2′s green and blue bands, are used to fit the spectral data with ICESat-2 height profiles. After water depth mapping using the trained model, independent ICESat-2 point clouds are used to validate the Sentinel-2 derived bathymetry. The RMSE values of the three models using the weighted average of multiple images for these six islands are within 0.50–0.90 m in 0–15 m deep. We also demonstrate that a synthesis of satellite laser altimetry and optical remote sensing can produce SDB results that potentially meet the requirement of category C in Zones of Confidence (ZOC) of the Electronic Navigational Chart (ENC) in 0–8 m deep. It is foreseen that ICESat-2 will be a helpful tool for mapping coastal and shallow waters around the world especially where bathymetric data are unavailable.

为了获得沿海地区的浅水测深，一种常见的方法是部署扫描机载测深光探测和测距 (LiDAR) 系统或船载测深仪进行地面勘测。然而，卫星遥感的最新进展，包括冰、云和陆地高程卫星 2 (ICESat-2)，为生成卫星测深 (SDB) 提供了新工具。ICESat-2 上的关键有效载荷是高级地形激光高度计系统 (ATLAS)，这是一种微脉冲、光子计数 LiDAR 系统，可同时以 10 kHz 的脉冲速率发射六个独立的 532 nm 光束。然而，尽管分辨率很高，但测深的主要限制是 ICESat-2 仅提供沿轨道高度剖面，在平行地面轨道之间留下观测间隙。

本研究旨在结合ICESat-2和Sentinel-2光学数据，推导出南海六个岛礁的浅水测深（深度<20 m）。地理参考光子的 ICESat-2 ATL03 点云首先被过滤以确定沿地面轨迹的海底高程。结果表明，与来自机载 LiDAR 活动的独立观测结果相比，均方根误差 (RMSE) 为 0.26–0.61 m。接下来，三个半经验函数，即修正线性/多项式/指数比率模型，其内核由 Sentinel-2 的绿色和蓝色波段之间的对数比形成，用于将光谱数据与 ICESat-2 高度剖面拟合. 使用训练模型绘制水深后，使用独立的 ICESat-2 点云来验证 Sentinel-2 导出的测深。使用这六个岛屿的多幅图像的加权平均值的三个模型的RMSE值在0-15 m深的0.50-0.90 m内。我们还证明了卫星激光测高和光学遥感的综合可以产生可能满足类别要求的 SDB 结果C在 0–8 m 深的电子航海图 (ENC) 的置信区 (ZOC) 中。可以预见，ICESat-2 将成为绘制全球沿海和浅水区地图的有用工具，尤其是在无法获得测深数据的情况下。