Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorith...
Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Contents
The spatio-temporal dynamism of sediment discharge (Qs) in rivers is influenced by various natural and anthropogenic factors. Unfortunately, most rivers are only monitored at a limited number of stations or not gauged at all. Therefore, this study aims to provide a remote-sensing-based alternative for Qs monitoring. The at-a-station hydraulic geome...
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Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms
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TN_cdi_doaj_primary_oai_doaj_org_article_ddf3f6d0dea84c9dad139b95164f043f
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_ddf3f6d0dea84c9dad139b95164f043f
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ISSN
2306-5338
E-ISSN
2306-5338
DOI
10.3390/hydrology9050088
