Remote Sensing Bathymetry of Nearshore Island Reefs via an Enhanced Dual-Stream Mixture Density Network

High-resolution bathymetry is critical for nearshore reefs, navigation, and island engineering. This paper proposes an Enhanced Mixture Density Network (EMDN) using dual-stream feature disentanglement and mixed total variance regularization to improve both accuracy and reliability of satellite-derived bathymetry (SDB). Validated with ICESat-2 and Sentinel-2 data over island reefs in the South China Sea and Hawaii, EMDN achieves RMSEs of 1.20 m, 1.24 m, and 3.71 m at Ganquan, Guangjin, and West Molokai, with the lowest mean uncertainties (0.76 m, 0.75 m, 2.46 m). Comparisons with the evaluated baselines demonstrate improved bathymetric accuracy and lower CRPS values, together with sharper prediction intervals and competitive calibration, highlighting the potential of EMDN for nearshore reef bathymetric mapping.