An inversion method of subsurface thermohaline field based on deep learning and remote sensing data-Reference-Cited by-同舟云学术

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An inversion method of subsurface thermohaline field based on deep learning and remote sensing data

Published:2023-04-11 Issue: Volume: Page:1-24
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Guo Quan¹,Li Yunbo²,Zhang Xuefeng¹,Ouyang Zhuxin¹,Li Zukun¹,Wang Yi¹,Cao Lingjuan¹,Han Leng³,Zhang Dianjun¹

Affiliation:

1. School of Marine Science and Technology, Tianjin University, Tianjin, China

2. Command Support Group of the Naval Staff Gevern-ment, Hydrometeorological Research Institute, Beijing, China

3. Tianjin Navigation Instrument Research Institute, Remote Sensing Research Institute, Tianjin, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2192880

Reference36 articles.

1. A Review of Ocean/Sea Subsurface Water Temperature Studies from Remote Sensing and Non-Remote Sensing Methods

2. Global warming increases the frequency of river floods in Europe

3. Estimation of ocean subsurface thermal structure from surface parameters: A neural network approach

4. MULTILAYER PERCEPTRONS TO APPROXIMATE COMPLEX VALUED FUNCTIONS

5. Distinctive climate signals in reanalysis of global ocean heat content

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