Automatic decision support system based on SAR data for oil spill detection

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 det...

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Vydáno v:	Computers & geosciences Ročník 72; s. 184 - 191
Hlavní autoři:	Mera, David, Cotos, José M., Varela-Pet, José, G. Rodríguez, Pablo, Caro, Andrés
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.11.2014
Témata:	Adaptive threshold Algorithms Automation coasts computers Decision support system Decision support systems Emergencies Iberian Peninsula international trade monitoring oceans Oil spills pollution SAR sea transportation Shape characterization shipping Spillage Synthetic aperture radar wind ANE, Europe, Iberian Peninsula ANE, Spain, Galicia Iberian Peninsula Adaptive threshold Decision support system SAR Shape characterization Oil spills
ISSN:	0098-3004, 1873-7803
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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 25% of the system processing time. •An automatic oil spill detection system based on SAR images was developed.•A database with confirmed oil spills was used to develop the system.•Image testing revealed up to 95.1% candidate labeling accuracy.•Two classifiers were compared from the labeling accuracy viewpoint.•The processing time was optimized via shared memory parallelization techniques.
AbstractList	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 25% of the system processing time. 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 25% of the system processing time. •An automatic oil spill detection system based on SAR images was developed.•A database with confirmed oil spills was used to develop the system.•Image testing revealed up to 95.1% candidate labeling accuracy.•Two classifiers were compared from the labeling accuracy viewpoint.•The processing time was optimized via shared memory parallelization techniques.
Author	Mera, David G. Rodríguez, Pablo Caro, Andrés Cotos, José M. Varela-Pet, José
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SubjectTerms	Adaptive threshold Algorithms Automation coasts computers Decision support system Decision support systems Emergencies Iberian Peninsula international trade monitoring oceans Oil spills pollution SAR sea transportation Shape characterization shipping Spillage Synthetic aperture radar wind
Title	Automatic decision support system based on SAR data for oil spill detection
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