<![CDATA[Mapping the extent and quantifying oil slick in ocean spills is one of the major objectives for monitoring and clean-up programs. Hyperspectral sensors are among the few remote sensing tools with potential for quantifying hydrocarbon oil on water and on other background substrates. At present, methods used to process hyperspectral data for quantifying hydrocarbon oil relies on delineating shapes and wavelength position of key diagnostic features within shortwave infrared (SWIR), particularly at 1.73µm and 2.30µm, which are often affected by the spectral features from the background substrates. Rather than the shape, the absorption maxima of hydrocarbon diagnostic features has shown potential for quantifying oil slick abundance classes via the Hydrocarbon Spectral Slope index (HYSS). In this research, the discriminative power of HYSS index for quantifying ocean oil slick is demonstrated, using Advance Visible and Infrared Imaging Spectrometer (AVIRIS) data from the 2010 Deep-water Horizon (DHW) spill from the Macondo well-head in the Gulf of Mexico. The results suggest good discrimination of oil and water as well as quantification of the oil slick into different oil abundance classes, representing different oil-water ratio and/or thickness. The validation of HYSS results shows good agreement with visual records of the spill within the image scene. Five oil abundance classes were discernible from studied AVIRIS scenes. These results were obtained empirically, without site-specific reference spectra, suggestive of a potential index for rapid broad area search. Change detection statistics of oil coverage at three separate intersects (ITT 1, ITT 2, and ITT 3) with before and after image coverage show reduced oil coverage percentages of 70%, 11.5%, and 0% respectively. These percentage reductions are in agreement with visual display of oil coverage as affected by dispersion induced by ocean currents and chemical dispersant application within the respective time lags of these image data acquisition.]]>
