# Comparison of Oil Spill Classifications Using Fully and Compact Polarimetric SAR Images
## 1 Introduction  
Oil spill is one of the most significant sources of marine pollution. In recent years, a series of accidents continually took place and threatened the marine environment. In April 2010, during the Deepwater Horizon (DWH) accident, approximately 780,000 m\({}^{3}\) of oil, methane or other fluids were released into the Gulf of Mexico. In 2011, approximately 700 barrels of crude oil were leaked into the Bohai Sea, and about 2500 barrels of mineral oil-based mud became deposited on the seabed. In December 2013, during an accident caused by a broken oil pipe, crude oil leaked into the coastal area of Qingdao, Shandong province, and covered approximately 1000 m\({}^{2}\) of the sea surface. In addition, a large proportion of oil spills are caused every year by deliberate discharges from tankers or cargos, for the reason that there are still vessels that secretly clean their tanks or engine before entering the harbor. These accidents and illegal acts cause damage to the coastal ecosystem, emphasizing the importance of detecting oil spills in their early stages. Although remote sensing with optical sensors can be used in oil spill detection, they are unavoidably restricted by weather and light conditions. Therefore, satellite synthetic aperture radar (SAR) data from ERS-1/2 (European Remote Sensing Satellites), ENVISAT (Environmental Satellite), ALOS (Advanced Land Observing Satellite), RADARSAT-1/2 and TerraSAR-X have been widely used to detect and monitor oil spills [1; 2; 3; 4; 5; 6; 7; 8] due to the large spatial coverage, all-weather conditions and imaging capability during day-night times [9]. In addition, airborne SAR sensors, such as Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) developed by JPL at L-band and E-SAR (developed by DLR), have proven their potential for scientific research on ocean or land [10; 11]. In SAR images, the detection of oil slick on the sea surface relies on the detection/quantification of its attenuation of Bragg scattering on the sea surface. When Bragg scattering happens, the signals from different sea surface facets interfere with each other. Moreover, according to the composite sea surface model, the roughness of the sea surface can be seen as small-scale capillary waves (contributing to Bragg scattering) superimposed on large-scale gravity waves. An illustration of this model can be seen in Figure 1. The sea surface of the oil-covered region appears smoother than its surrounding area. This is because the Bragg scattering of these areas is suppressed by the presence of hydrocarbons. However, the main backscatter from the sea surface is contributed by Bragg scattering. As a result, in SAR images the oil slick-covered area can usually be detected as a very dark (low backscattered) area. In SAR images, the backscattered signal from oil spill is very similar to that from other ocean phenomena called \"look-alikes\" [1]. In recent years it has been demonstrated by theoretical and experimental studies the benefit of the polarimetric SAR paradigm, which explore the polarimetric SAR measurements and a proper electromagnetic modelling to distinguish light-damping surfactants from heavy-damping ones. This can be exploited as one case to sort out most of the look-alikes that are typical, such as biogenic films (slicks that are produced by marine organisms, such as fishes, algae, etc. ), which normally cause very little harm to the marine environment [12; 13]. The feasibility of polarimetric SAR-based oil spill classifications relies on the fact that the polarimetric mechanisms for oil-free and oil-covered sea surface are largely different [14]. Before the availability of polarimetric observations, hydrocarbons and biogenic slicks were difficult to distinguish because they damped the short gravity-capillary waves with almost the same strength [15].