International Journal of Applied Earth Observations and Geoinformation (Aug 2024)
A novel bathymetric signal extraction method for photon-counting LiDAR data based on adaptive rotating ellipse and curve iterative fitting
Abstract
Equipped with the Advanced Topographic Laser Altimeter System (ATLAS) of 532 nm, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) is enabled to penetrate the water surface to retrieve water depth information at certain depths. However, signal photon extraction is significantly impacted by noise and varying terrain conditions, particularly in deep water regions with weaker signal photons. To address these challenges, this study proposed a novel bathymetric signal extraction method for ICESat-2/ATLAS data based on adaptive rotating ellipse and B-spline curve iterative filtering. First, raw photons are segregated into water surface and bottom photons using the specular return removal algorithm and combined with the RANdom SAmple Consensus (RANSAC) algorithm to derive water surface elevation. Second, our method employs the modified Ordering Points to Identify the Clustering Structure (OPTICS) with adaptive variable ellipse and B-spline curve iterative filtering to detect bottom signal photons. Following refraction and tidal corrections, water depth is computed. Finally, the bathymetric accuracy of the proposed algorithm is evaluated using manually labeled photons and airborne bathymetric LiDAR data. The experimental results indicate the proposed algorithm’s superior F_score value, which increased by about 6.6 % and 4.1 % compared with the high-confidence photons and Adaptive Variable Ellipse Filtering Bathymetric Method (AVEBM). Moreover, the Mean Absolute Deviation (MAE) of bathymetric accuracy is 0.47 m, the Root Mean Square Error (RMSE) is 0.55 m, and Coefficient of Determination (R2) of bathymetric accuracy is 0.93. The proposed method effectively extracts signal photons and provides accurate water depth for nearshore bathymetry estimation.
