Abstract
Use of polarimetric SAR data for offshore pollution monitoring is relatively new and shows great potential for operational offshore platform monitoring. This paper describes the development of an automated oil spill detection chain for operational purposes based on C-band (RADARSAT-2) and X-band (TerraSAR-X) fully polarimetric images, wherein we use polarimetric features to characterize oil spills and look-alikes. Numbers of near coincident TerraSAR-X and RADARSAT-2 images have been acquired over offshore platforms. Ten polarimetric feature parameters were extracted from different types of oil and ‘look-alike’ spots and divided into training and validation dataset. Extracted features were then used to develop a pixel based Artificial Neural Network classifier. Mutual information contents among extracted features were assessed and feature parameters were ranked according to their ability to discriminate between oil spill and look-alike spots. Polarimetric features such as Scattering Diversity, Surface Scattering Fraction and Span proved to be most suitable for operational services.
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