Distinguishing Mineral Oil Slicks from Low-Wind Areas Using High-SNR Synthetic Aperture Radar

Journal article, 2026

We propose a method for distinguishing oil slicks from radar-dark, oceanic low wind areas using single acquisitions of high-SNR airborne and spaceborne SAR imagery. Airborne data was acquired by DLR's F-SAR X- and L-band SAR instrument during a controlled release, oil-on-water campaign, and by NASA's UAVSAR L-band SAR instrument over the Aleutian Islands in Alaska and the Coal Oil Point seep field near Santa Barbara, California. The spaceborne imagery consists of five RADARSAT-2 C-band SAR scenes containing either low-wind zones or mineral and plant oil, three of which were acquired during controlled releases in the North Sea. A RADARSAT-2 scene containing grease ice is included to demonstrate the potential of the proposed method to discriminate between oil slick and other look-alike types. The proposed product, referred to as KS index maps, is based on the Kolmogorov-Smirnov test statistic and is used as a measure of separability between ensembles of pixels inside vs. outside a radar-dark area. We use the theoretical Polarimetric Two-Scale Model to interpret the physical basis on which our method distinguishes between radar-dark oil slicks and low-wind zones relative to nearby open water in higher wind areas. KS index values for oil slick are consistently between -1 and 0 and KS index values for low-wind zones (and grease ice) are consistently between 0 and +1. The method is suitable for near-real-time implementation to aid oil spill response.