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Automatic detection of oil spills from SAR images / F. Nirchio in International Journal of Remote Sensing IJRS, vol 26 n° 6 (March 2005)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 26 n° 6 (March 2005) . - pp 1157 - 1174 Titre : Automatic detection of oil spills from SAR images Type de document : Article/Communication Auteurs : F. Nirchio, Auteur ; M. Sorgente, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1157 - 1174 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] classification [Termes IGN] détection automatique [Termes IGN] image ERS-SAR [Termes IGN] modèle stochastique [Termes IGN] pétrole [Termes IGN] pollution des mers [Termes IGN] risque environnemental [Termes IGN] surveillance écologique Résumé : (Auteur) A probalistic method has been developed that distinguishes oil spills from other similar sea surface features in synthetic aperture radar (SAR) images. It considers both the radiometric and geometric characteristics of the areas being tested. In order to minimize the operator intervention, it adopts automatic selection criteria to extract the potentially polluted areas from the images. The method has an a priori percentage of correct classification higher than 90% on the training dataset ; the performance is confirmed on a different dataset of verified slicks. Some analysis have been conducted using images with different radiometric and geometric resolutions to test its suitability with SAR images different from European Remote Sensing (ERS) satellite ones. The system and its ability to detect and classify oil and non-oil surface features are described. Starting from a set of verified oil spills detected offshore and over coastline, the ability of SAR to reveal oil spills is tested by analysing wind intensity, deduced from the images itself, and the distance from the coast. Numéro de notice : A2005-146 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331326558 En ligne : https://doi.org/10.1080/01431160512331326558 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27284 [article]

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