SAR Polarimetry to Observe Oil Spills

A study on sea oil spill observation by means of polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on the use of a polarimetric constant false alarm rate filter to detect dark patches over SAR images. Then, the target decomposition theorem is exploited to distinguish oil spills and look-alikes. Experiments are conducted on polarimetric SAR data acquired during the SIR-C/X-SAR mission on October 1994. The data were processed and calibrated at the Jet Propulsion Laboratory, National Aeronautics and Space Administration. Results show that the new polarimetric approach is able to assist classification

I. Introduction

Sea oil spill pollution is a matter of great concern since it affects the life cycle and the human food chain. Remote sensing can be of great help in limiting the occurrence of such events and improving oil spill observation [1]. It can provide data at relatively low cost and a continuous and synoptical sea observation. Microwave remote sensing is of special importance due to its practical insensitivity to cloud cover and other atmospheric phenomena. The synthetic aperture radar (SAR) is the key sensor because of its high spatial resolution. Generally, single polarimetric SARs are used [1]. Physically, oil spill detection is possible since oil slicks damp the short gravity and capillary waves that are responsible for the backscattered electromagnetic field at the SAR: a dark patch is generated over the SAR image. Unfortunately, other physical phenomena, known as look-alikes, may generate dark patches over the SAR images [1].