Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms
AbstractThis paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject. View Full-Text
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Topouzelis, K.N. Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms. Sensors 2008, 8, 6642-6659.
Topouzelis KN. Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms. Sensors. 2008; 8(10):6642-6659.Chicago/Turabian Style
Topouzelis, Konstantinos N. 2008. "Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms." Sensors 8, no. 10: 6642-6659.