Natural oil Seep Location Estimation in SAR images using direct and contextual information

The Automatic oil Seep Location Estimator (ASLE) described in this paper is a system that can automatically estimate the locations of potential oil seeps using SAR images. The ASLE segments dark areas in SAR images, calculates direct features related to geometry and backscatter as well as contextual features like wind speed and direction for each dark object and uses them to classify the object as either a natural oil slick or a look-alike. The classification scheme has been implemented using a rule-based approach. The slick origins are detected and clustered together spatially to detect the feeding seep locations. A preliminary dataset of 25 images from ENVISAT´s Advanced Synthetic Aperture Radar (ASAR) was used to test the algorithm. The results show the addition of contextual information helps reduce false positives in automatic slick detection.