Oil spill mapping is a very challenging problem in marine environmental monitoring. In this paper, the potential of hyperspectral image classification for mapping oil spills is comprehensively investigated. First, several representative hyperspectral image classification methods are reviewed in a general framework. Second, three oil spill mapping cases are designed to analyze the performance of different classification methods in detecting the spatial distribution, classifying the type, and estimating the thickness of oil spills. Finally, the experimental results are analyzed in detail, and some conclusions are given, which bring a comprehensive understanding to scholars who are interested in the fields of hyperspectral remote sensing and oil spill mapping.
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Kang et al. (2022) studied this question.
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