Seafloor Topography Predicted from SWOT Gravity Data by Deep Neural Network in the Northwestern Pacific Ocean

This study combines SWOT marine gravity field data with single-beam shipborne depth to construct seafloor topography models in the Northwestern Pacific using the deep neural network method (DNN) ===========================================Preprocesss-Shipborne_depth DATA: singlbeam.xyz multibeam.xyz checkpoints.xyz SWOT_03:https://topex.ucsd.edu/pub/GEBCO_2024/GEBCO_08:https://www.gebco.net/ ===========================================DNN CODE:deep neural network.pyDATA:Training_Dataset_SWOT.txt Ind.txt sea.zip===========================================Bathymetry model GGM_SWOT SAS_SWOT DNN_SWOT