Automatic decision support system based on SAR data for oil spill detection
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|Title:||Automatic decision support system based on SAR data for oil spill detection
Cotos, José M.
Rodríguez, Pablo G.
|Affiliation:||Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías da Información
Universidade de Santiago de Compostela. Instituto de Investigacións Tecnolóxicas
|Subject:||Decision support system | Oil spills | SAR | Adaptive threshold | Shape characterization ||
|Date of Issue:||2014-07-31
|Citation:||Mera, D., Cotos, J., Varela-Pet, J., G. Rodríguez, P. and Caro, A. (2014). Automatic decision support system based on SAR data for oil spill detection. Computers & Geosciences, 72, pp.184-191.
|Abstract:||Global trade is mainly supported by maritime transport, which generates important pollution problems. Thus, effective surveillance and intervention means are necessary to ensure proper response to environmental emergencies. Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillages on the oceans surface. Several Decision Support Systems have been based on this technology. This paper presents an automatic oil spill detection system based on SAR data which was developed on the basis of confirmed spillages and it was adapted to an important international shipping route off the Galician coast (northwest Iberian Peninsula). The system was supported by an adaptive segmentation process based on wind data as well as a shape oriented characterization algorithm. Moreover, two classifiers were developed and compared. Thus, image testing revealed up to 95.1% candidate labeling accuracy. Shared-memory parallel programming techniques were used to develop algorithms in order to improve above a 25% of the system processing time|
|Description:||This is the accepted manuscript of the following article: Mera, D., Cotos, J., Varela-Pet, J., G. Rodríguez, P. and Caro, A. (2014). Automatic decision support system based on SAR data for oil spill detection. Computers & Geosciences, 72, pp.184-191
|Rights:||© 2014 Elsevier Inc. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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