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Deep learning for extracting water body from Sentinel-2 MSI imagery
2021<p>Deep learning has a good capacity of hierarchical feature learning from unlabeled remote sensing images. In this study, the simple linear iterative clustering (SLIC) method was improved to segment the image into good quality super-pixels.
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Soil Salinity Mapping Using Machine Learning Algorithms with the Sentinel-2 MSI in Arid Areas, China
Remote Sensing, 2021Jiaqiang Wang +2 more
exaly
Floods automatic rapid mapping through Sentinel-2 MSI multitemporal data
Floods are widespread natural disasters on Earth affecting the planet with increasing frequency and intensity. Climate changes are responsible of the increasing number of heavy and persistent rains generating these destructive events often resulting in fatalities, injuries, and extensive infrastructural damages.Valeria Satriano +3 more
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Deep Learning-Based Automatic Extraction of Cyanobacterial Blooms from Sentinel-2 MSI Satellite Data
Remote Sensing, 2022Danfeng Hong +2 more
exaly
A PLSR model to predict soil salinity using Sentinel-2 MSI data
Open Geosciences, 2021Ghada Sahbeni
exaly