Abstract
In this study, advanced techniques for oil spill detection and oil spill type identification using hyperspectral (HSI) AVIRIS data are presented. The new HSI techniques make it possible to model water–leaving radiances from different types of oil slicks. Several methods are used including Spectral Angle Mapper (SAM) and Partial Unmixing (PU) techniques. Our study is focusing on target identification for oil slick type and signature feature analysis for oil spill thickness. We show that oil spills on sea water can be clearly identified. In addition, oil spill thickness and slick types at different stages could be identified by analyzing the spectral features of AVIRIS data.
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