Mapping oil spills on sea water using spectral mixture analysis of hyperspectral image data

During the last years, several terrestrial ecosystems have suffered from large spill oil events threatening coastal habitats and species. Some recent examples include the 2002 Prestige tanker oil spill in Galicia, Northern Spain, as well as repeated oil spill leaks evidenced in the Santa Barbara coastline in California, and the Patuxent river (Chesapeake watershed) in Maryland. Both spaceborne and airborne hyperspectral sensors allow detailed identification of materials, and very accurate (sub-pixel) estimates of their fractional abundance covers. In the event of an oil spill, the information produced by remotely sensed hyperspectral instruments can be used to design an effective environmental oil spill protection and response plan, which could help to reduce the environmental consequences of the spill and cleanup efforts, as well as to protect human life. In this paper, we discuss a novel automated hyperspectral target detection technique for determining the level of oil contamination of polluted areas in the shoreline. The method is based on the simultaneous use of spatial and spectral information by extended mathematical morphology operations. Both simulated and real hyperspectral data, collected over polluted areas, are used in this work to illustrate the effectiveness of the proposed approach.