Enhancing bathymetric prediction by integrating gravity and gravity gradient data with deep learning

Enhancing bathymetric prediction by integrating gravity and gravity gradient data with deep learning

This study aims to enhance the spatial resolution and accuracy of bathymetric prediction by integrating Gravity Anomaly (GA) and Vertical Gravity Gradient Anomaly (VGG) data with a dual-channel Backpropagation Neural Network (BPNN). The seafloor topography of the Izu-Ogasawara Trench in the Western...

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Bibliographic Details
Main Authors: Junhui Li, Nengfang Chao, Houpu Li, Gang Chen, Shaofeng Bian, Zhengtao Wang, Aoyu Ma
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Marine Science
Subjects:
seafloor topography
BPNN
gravity anomaly
vertical gravity gradient
Izu-Ogasawara Trench
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2024.1520401/full
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