Oil-Spill-Response-Oriented Information Products Derived From a Rapid-Repeat Time Series of SAR Images

New quantitative and semiautomated methods for analyzing oil slick evolution using a time series of $L$-band synthetic aperture radar (SAR) images with short repeat time are developed and explored. In this study, two methods that are complementary in terms of identifying temporal changes within an oil slick are presented. The two methods reflect two ways of evaluating the oil slicks. The first method identifies regions within the slick that show persistently high damping ratio (the contrast between clean sea and oil intensity), using higher damping values as a proxy for increasing oil thickness. This method also weights the age of the scenes as the algorithm incorporates new images. The second method outputs the short-term drift pattern and the changes in the damping ratios and copolarization ratios between two scenes, proxies for thickness, and emulsification. Both methods can aid in identifying regions of high priority for oil recovery. Due to the simplicity of the methods, they can be adapted to time-series data from different types of sensors, e.g., optical and SAR imagery. The methods are demonstrated on three $L$-band uninhabited aerial vehicle SAR UAVSAR time series acquired in November 2016 over a persistent seep in the Mississippi Canyon Block 20 of the Gulf of Mexico. The results of the two methods clearly show the movement and the weathering of the oil as a function of both time and location.

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