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HAZARDOUS NOXIOUS SUBSTANCE DETECTION BASED ON HYPERSPECTRAL REMOTE SENSING TECHNIQUE

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Authors

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

Issue Date
2020-09
Publisher
IEEE
Citation
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, pp.2165-2168
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.
ISSN
2153-6996
URI
https://hdl.handle.net/10371/186411
DOI
https://doi.org/10.1109/IGARSS39084.2020.9324029
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