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Hazardous Noxious Substance Detection Based on Hyperspectral Remote Sensing Technique

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dc.contributor.author박재진-
dc.contributor.author박경애-
dc.contributor.authorPierre-Yves Foucher-
dc.contributor.authorPhilippe Deliot-
dc.contributor.authorStephane Le Floch-
dc.contributor.author김태성-
dc.contributor.author오상우-
dc.contributor.author이문진-
dc.date.accessioned2021-12-08T07:42:15Z-
dc.date.available2021-12-08T07:42:15Z-
dc.date.issued20201001-
dc.identifier.urihttps://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/2340-
dc.description.abstractHazardous 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 HNSand 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.-
dc.language영어-
dc.language.isoENG-
dc.titleHazardous Noxious Substance Detection Based on Hyperspectral Remote Sensing Technique-
dc.title.alternativeHazardous Noxious Substance Detection Based on Hyperspectral Remote Sensing Technique-
dc.typeConference-
dc.citation.titleIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2020)-
dc.citation.volume1-
dc.citation.number1-
dc.citation.startPage1-
dc.citation.endPage4-
dc.citation.conferenceNameIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2020)-
dc.citation.conferencePlace미국-
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