A Denoising Methodology for Detecting ICESat-2 Bathymetry Photons Based on Quasi Full Waveform

Abstract

Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) photon counting data are widely used in nearshore bathymetry. However, a large number of noisy photons unavoidably exist in the acquired photon data, and photon denoising is necessary to accurately extract the underwater signal photons. Based on the phenomenon that the number of photons increases at the target object, a methodology for detecting ICESat-2 bathymetry photons based on quasi full waveform is proposed. First, the ICESat-2 photon data are split at certain intervals to extract the sea surface and seafloor height photons within each interval. Second, a double-peaked Gaussian function is utilized to fit the photon heights in each interval to determine the sea surface and seafloor heights. Third, sea surface and seafloor height photons for each interval are connected along the track direction to generate sea surface and seafloor datums. Finally, the optimal buffer distance is calculated and the buffer is created to filter the photons, and then, the refraction correction is applied to the seafloor photons. ICESat-2 data from Vieques Island and Saint Croix Island are selected for the experiment and the results are compared with in situ bathymetry data. The results show that the mean absolute error (MAE) of the bathymetry results extracted by the proposed method ranged from 0.16 to 0.30 m and the RMSE ranged from 0.24 to 0.32 m in different areas. Compared with density-based spatial clustering of applications with noise (DBSCAN), ordering points to identify the clustering structure (OPTICS), and adaptive elevation difference thresholding algorithm (AEDTA), the proposed method accurately recognizes the signal photons for different densities of photon data and different complexities of seafloor topography, and the extracted signal photons are complete and continuous, showing excellent robustness. By selecting suitable split spacing along the track direction and histogram separation spacing, the proposed method in this study achieves excellent performance in bathymetry extraction.