Hazardous Noxious Substance Detection Based on Hyperspectral Remote Sensing Technique

Jae-Jin Park, Kyung-Ae Park, Pierre-Yves Foucher, Philippe Déliot, Stéphane Le Floch, Tae-Sung Kim, Sangwoo Oh, Moonjin Lee

Abstract: Hazardous Noxious Substance (HNS) is transported entirely through large vessels, so there is always a potential risk of marine HNS spills. In the event of an HNS accident, it can cause enormous human and property damage, so prompt detection is required. However, there is a limit to human access by ship, we need to use remote sensing data. In this study, ground experiments using hyperspectral cameras were performed to construct a spectral library of HNS. We classified the HNS and non-HNS by applying the hyperspectral mixture algorithm, and presented the HNS detection probability for every pixel by calculating the spectrum-based abundance fraction. The results of this study are expected to be used to estimate the extent of HNS spill in the event of a marine HNS accident.