Title: Spectral analysis for oil spill identification using hyperspectral data
Authors: Foudan Salem, Menas Kafatos
Addresses: George Mason University, USA. ' George Mason University, USA
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.
Keywords: spectral analysis; oil spill identification; oil spills; hyperspectral data; oil spill detection; oil slicks; oil spill thickness; seawater; AVIRIS.
Interdisciplinary Environmental Review, 2004 Vol.6 No.2, pp.117 - 131
Published online: 13 May 2013 *
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