Continuous operational monitoring by means of remote sensing contributes significantly towards less occurrence of oil spills over European waters however, operational activities show regular occurrence of accidental and deliberate oil spills over the North Sea, particularly from offshore platform installations. Since the areas covered by oil spills are usually large and scattered over the North Sea, satellite remote sensing particularly Synthetic Aperture Radar (SAR) represents an effective tool for operational oil spill detection. This paper describes the development of a semi-automated approach for oil spill detection, optimized for near real time offshore platform sourced pollution monitoring context. Eight feature parameters are extracted from each segmented dark spot. The classification algorithm is based on artificial neural network. An initial evaluation of this methodology has been carried out on 156 TerraSAR-X images. Wind and current history information also have been analyzed for particular cases in order to evaluate their influences on spill trajectory.
Keywords: Marine pollution; Offshore platform monitoring; Oil spill detection; Synthetic aperture radar.
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