Offshore Oil Slick Detection: From Photo-Interpreter to Explainable Multi-Modal Deep Learning Models Using SAR Images and Contextual Data

Offshore Oil Slick Detection: From Photo-Interpreter to Explainable Multi-Modal Deep Learning Models Using SAR Images and Contextual Data

Ocean surface monitoring, emphasizing oil slick detection, has become essential due to its importance for oil exploration and ecosystem risk prevention. Automation is now mandatory since the manual annotation process of oil by photo-interpreters is time-consuming and cannot process the data collecte...

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Bibliographic Details
Main Authors: Emna Amri, Pierre Dardouillet, Alexandre Benoit, Hermann Courteille, Philippe Bolon, Dominique Dubucq, Anthony Credoz
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Remote Sensing
Subjects:
oil slicks
data fusion
offshore detection
SAR images
meteorological data
deep learning
Online Access:https://www.mdpi.com/2072-4292/14/15/3565

Internet

https://www.mdpi.com/2072-4292/14/15/3565

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