ICESat-2 bathymetric

When applied to datasets from the Great Barrier Reef in Australia, Oahu Island in the Hawaiian Islands, Ganquan Island, and Puerto Rico, the accuracy of the model is all above 0.9. Although the accuracy of underwater data denoising is slightly lower, with a denoising rate of over 0.6 at the same location, the results are still very valuable for practical applications. To verify the effectiveness of the MLP method, a comparative analysis was conducted between the DBSCAN algorithm and the confidence based classification method.

The results highlight the superiority of deep learning based methods. After refractive correction, the correlation coefficient exceeds 0. 80 observations were made between the extracted seabed depth data and actual depth measurements. In addition, the average absolute error is less than 1 m, and the root mean square error is less than 1. 0 meters, 2