Internal waves are widely distributed in the ocean, and their amplitude can reach hundreds of meters, affecting the ocean environment.
Remote sensing is a crucial method for observing internal waves in the ocean. However, inversion of internal wave amplitudes from remote sensing images is not available.
Recently, a research team led by Dr. LI Xiaofeng from the Institute of Oceanology, Chinese Academy of Sciences (IOCAS) applied artificial intelligence (AI) transfer learning techniques to integrate data from laboratory, buoy and remote sensing to study internal waves.
The study was published in Environmental remote sensing February 9.
Researchers applied in-situ remote sensing data and to establish a matched dataset for model training, and used AI transfer learning techniques to problem-solve different data sources and accurately reconstruct the three-dimensional structure of internal waves.
The internal solitary wave amplitude inversion model based on AI transfer learning is a two-step model. In the first step, transfer learning is applied to process different internal wave data sources. A bespoke ResNet-inspired modification called Short Connect is introduced. In the second stage, the model performs a bias correction of the results from the first stage using the density information of the real oceans.
“The model can invert the amplitude of internal waves by taking information extracted from satellite images as input, and the three-dimensional structure of internal waves can be reconstructed,” said Dr LI.
The related results demonstrate that the development of inversion models for complex marine phenomena based on big data of ocean information based on pure data is reliable and feasible.
“As a rapidly growing emerging technology, AI technology can establish rapid and direct mapping relationships in the study of complex marine phenomena,” said Dr. LI.
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Xudong Zhang et al, Retrieval of internal ocean wave amplitude from satellite images based on a data-driven transfer learning model, Environmental remote sensing (2022). DOI: 10.1016/j.rse.2022.112940
chinese academy of sciences
AI transfer learning techniques help study internal ocean waves (February 17, 2022)
retrieved 18 February 2022
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