Estimating Sea Surface Salinity in the East China Sea Using Satellite Remote Sensing and Machine Learning

Estimating Sea Surface Salinity in the East China Sea Using Satellite Remote Sensing and Machine Learning

Abstract Sea surface salinity (SSS) is a master variable in oceanography and important to understand marine biogeochemical and physical processes. In the East China Sea (ECS), a random forest based regression ensemble model (RF) was developed to estimate the SSS with a spatial resolution of ∼1 km ba...

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Bibliographic Details
Main Authors: Jing Liu, Richard G. J. Bellerby, Qing Zhu, Jianzhong Ge
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2023-11-01
Series:Earth and Space Science
Subjects:
sea surface salinity
random forest
remote sensing reflectance
East China Sea
sea surface temperature
Changjiang River discharge
Online Access:https://doi.org/10.1029/2023EA003230

Internet

https://doi.org/10.1029/2023EA003230

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