Automatic identification of oil spills on satellite images

Keramitsoglou, I; Cartalis, C; Kiranoudis, CT

dc.contributor.author	Keramitsoglou, I	en
dc.contributor.author	Cartalis, C	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:23:39Z
dc.date.available	2014-03-01T01:23:39Z
dc.date.issued	2006	en
dc.identifier.issn	1364-8152	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17070
dc.subject	Fuzzy logic	en
dc.subject	Marine pollution	en
dc.subject	Oil spills	en
dc.subject	Remote sensing	en
dc.subject	SAR	en
dc.subject	Sea surface	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Environmental	en
dc.subject.classification	Environmental Sciences	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Encoding (symbols)	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Imaging systems	en
dc.subject.other	Marine pollution	en
dc.subject.other	Remote sensing	en
dc.subject.other	Satellites	en
dc.subject.other	Synthetic aperture radar	en
dc.subject.other	Dynamic link library (dll)	en
dc.subject.other	MS Visual C++	en
dc.subject.other	Satellite images	en
dc.subject.other	Sea surface	en
dc.subject.other	Oil spills	en
dc.subject.other	algorithm	en
dc.subject.other	decision making	en
dc.subject.other	oil spill	en
dc.subject.other	remote sensing	en
dc.subject.other	satellite imagery	en
dc.subject.other	sea surface	en
dc.subject.other	Aegean Sea	en
dc.subject.other	Eurasia	en
dc.subject.other	Europe	en
dc.subject.other	Greece	en
dc.subject.other	Mediterranean Sea	en
dc.subject.other	Southern Europe	en
dc.title	Automatic identification of oil spills on satellite images	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.envsoft.2004.11.010	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.envsoft.2004.11.010	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	A fully automated system for the identification of possible oil spills present on Synthetic Aperture Radar (SAR) satellite images based on artificial intelligence fuzzy logic has been developed. Oil spills are recognized by experts as dark patterns of characteristic shape, in particular context. The system analyzes the satellite images and assigns the probability of a dark image shape to be an oil spill. The output consists of several images and tables providing the user with all relevant information for decision-making. The case study area was the Aegean Sea in Greece. The system responded very satisfactorily for all 35 images processed. The complete algorithmic procedure was coded in MS Visual C++ 6.0 in a stand-alone dynamic link library (dll) to be linked with any sort of application under any variant of MS Windows operating system. (c) 2004 Elsevier Ltd. All rights reserved.	en
heal.publisher	ELSEVIER SCI LTD	en
heal.journalName	Environmental Modelling and Software	en
dc.identifier.doi	10.1016/j.envsoft.2004.11.010	en
dc.identifier.isi	ISI:000237770000005	en
dc.identifier.volume	21	en
dc.identifier.issue	5	en
dc.identifier.spage	640	en
dc.identifier.epage	652	en