High-Precision Inversion of Shallow Bathymetry under Complex Hydrographic Conditions Using VGG19—A Case Study of the Taiwan Banks

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 5; p. 1257
• Main Authors: Cui, Jiaxin, Luo, Xiaowen, Wu, Ziyin, Zhou, Jieqiong, Wan, Hongyang, Chen, Xiaolun, Qin, Xiaoming
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2023
• Subjects: Accuracy; Algorithms; Artificial intelligence; Back propagation; Bathymeters; Bathymetry; Deep learning; Inversion; Machine learning; Marine environment; Mean square errors; Measurement techniques; Methods; multibeam sonar data; Neural networks; Propagation; Radar imaging; Remote sensing; Root-mean-square errors; Satellites; shallow bathymetry inversion; Shallow water; Simulation; Synthetic aperture radar; synthetic aperture radar image data; Topography; Underwater exploration; VGG model; China; Taiwan

Shallow bathymetry is important for ocean exploration, and the development of high-precision bathymetry inversion methods, especially for shallow waters with poor quality, is a major research aim. Synthetic aperture radar (SAR) image data benefit from a wide coverage, high measurement density, rapid...