Sea Surface Salinity Inversion Model for Changjiang Estuary and Adjoining Sea Area with SMAP and MODIS Data Based on Machine Learning and Preliminary Application

Sea Surface Salinity Inversion Model for Changjiang Estuary and Adjoining Sea Area with SMAP and MODIS Data Based on Machine Learning and Preliminary Application

Sea surface salinity (SSS) is one of the most important basic parameters for studying the oceanographic processes and is of great significance in identifying oceanic currents. However, for a long time, the salinity observation in the estuary and coastal waters has not been well resolved due to the t...

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Bibliographic Details
Main Authors: Xiaoyu Zhang, Mingfei Wu, Wencong Han, Lei Bi, Yongheng Shang, Yingchun Yang
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Remote Sensing
Subjects:
sea surface salinity
satellite remote sensing
inversion models
machine learning methods
Changjiang Estuary and adjacent sea area
Online Access:https://www.mdpi.com/2072-4292/14/21/5358

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