Application of the Method of Moment and Monte-Carlo Simulation to Extract Oil Spill Areas from Synthetic Aperture Radar Images

Abstract

Synthetic aperture radar (SAR) is a useful instrument to detect oil slicks on the sea surface. Generally, the algorithm for detection of oil slick in SAR images is based on the approach to distinguish the darker area compared to the surrounding area defined on the typical backscatter level. This value can calculate by scattering model using moment method and Monte-Carlo simulation for various conditions of surface roughness induced wind, oil-layer thickness, frequency, polarization and incidence angle. For the simulation, Automatic Weather System (AWS) were used to generate wind fields in SAR image area. The purpose of this study is that extraction of oil spill area from SAR images. For the extraction, radar backscattering value was calculated using scattering model, and it is used by threshold value for distinguishing between oil-covered and non-area in SAR images. In this study, oil thickness assumed by constant, and didn't take into account the direction of the wind. From this study results, we expect that automatic classification of oil slick features from lookalikes and detecting of seepage on sea surface.