期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 18, 期 4, 页码 573-576出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2020.2983826
关键词
Image segmentation; Ocean temperature; Robustness; Temperature sensors; Monitoring; Clustering algorithms; Sea measurements; Sea surface temperature (SST) images; upwelling; upwelling identification and extraction; upwelling index
类别
资金
- French-Moroccan Partenariats Hubert Curien (PHC)-Toubkal [TBK/16-24, PPR2-6]
Analyzing and studying coastal upwelling using sea surface temperature (SST) satellite images is a common and cost-effective procedure. A robust method based on the Ekman theory is proposed to identify upwelling regions along the north-west African margin, overcoming issues encountered in previous methods. This method can serve as a framework to study and monitor the spatio-temporal variability of upwelling phenomenon in the region.
Analysis and study of coastal upwelling using sea surface temperature (SST) satellite images is a common procedure because of its coast effectiveness (economic, time, frequency, and manpower). Developing on the Ekman theory, we propose a robust method to identify the upwelling regions along the north-west African margin. The proposed method comes to overcome the issues encountered in a recent method devoted for the same purpose and for the same upwelling system. Afterward, we show how our method can serve as a framework to study and monitor the spatio-temporal variability of the upwelling phenomenon in the studied region.
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