{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T07:09:48Z","timestamp":1783062588813,"version":"3.54.6"},"reference-count":38,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,18]],"date-time":"2021-01-18T00:00:00Z","timestamp":1610928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Development of Management Technology for HNS Accident","award":["20150340"],"award-info":[{"award-number":["20150340"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With an increase in the overseas maritime transport of hazardous and noxious substances (HNSs), HNS-related spill accidents are on the rise. Thus, there is a need to completely understand the physical and chemical properties of HNSs. This can be achieved through establishing a library of spectral characteristics with respect to wavelengths from visible and near-infrared (VNIR) bands to shortwave infrared (SWIR) wavelengths. In this study, a ground HNS measurement experiment was conducted for artificially spilled HNS by using two hyperspectral cameras at VNIR and SWIR wavelengths. Representative HNSs such as styrene and toluene were spilled into an outdoor pool and their spectral characteristics were obtained. The relative ratio of HNS to seawater decreased and increased at 550 nm and showed different constant ratios at the SWIR wavelength. Noise removal and dimensional compression procedures were conducted by applying principal component analysis on HNS hyperspectral images. Pure HNS and seawater endmember spectra were extracted using four spectral mixture techniques\u2014N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA). The accuracy of detection values of styrene and toluene through the comparison of the abundance fraction were 99.42% and 99.56%, respectively. The results of this study are useful for spectrum-based HNS detection in marine HNS accidents.<\/jats:p>","DOI":"10.3390\/rs13020318","type":"journal-article","created":{"date-parts":[[2021,1,20]],"date-time":"2021-01-20T03:34:25Z","timestamp":1611113665000},"page":"318","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Hazardous Noxious Substance Detection Based on Ground Experiment and Hyperspectral Remote Sensing"],"prefix":"10.3390","volume":"13","author":[{"given":"Jae-Jin","family":"Park","sequence":"first","affiliation":[{"name":"Department of Science Education, Seoul National University, Seoul 08826, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8899-7201","authenticated-orcid":false,"given":"Kyung-Ae","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Earth Science Education\/Research Institute of Oceanography, Seoul National University, Seoul 08826, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0435-4573","authenticated-orcid":false,"given":"Pierre-Yves","family":"Foucher","sequence":"additional","affiliation":[{"name":"Department of Theoretical and Applied Optics, Office National d\u2019Etudes et Recherches A\u00e9rospatiales, 31055 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philippe","family":"Deliot","sequence":"additional","affiliation":[{"name":"Department of Theoretical and Applied Optics, Office National d\u2019Etudes et Recherches A\u00e9rospatiales, 31055 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5794-7284","authenticated-orcid":false,"given":"Stephane Le","family":"Floch","sequence":"additional","affiliation":[{"name":"Department of Research, Centre de Documentation de Recherche et D\u2019expe\u2019Rimentations sur les Pollutions Accidentelles des Eaux, 29200 Brest, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae-Sung","family":"Kim","sequence":"additional","affiliation":[{"name":"Maritime Safety and Environmental Research Division, Korea Research Institute of Ships and Ocean Engineering, Daejeon 34103, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1545-0253","authenticated-orcid":false,"given":"Sangwoo","family":"Oh","sequence":"additional","affiliation":[{"name":"Maritime Safety and Environmental Research Division, Korea Research Institute of Ships and Ocean Engineering, Daejeon 34103, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4665-3333","authenticated-orcid":false,"given":"Moonjin","family":"Lee","sequence":"additional","affiliation":[{"name":"Maritime Safety and Environmental Research Division, Korea Research Institute of Ships and Ocean Engineering, Daejeon 34103, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.jclepro.2019.04.020","article-title":"Oil spills from global tankers: Status review and future governance","volume":"227","author":"Chen","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_2","first-page":"369","article-title":"Oil and planktonic ecosystems","volume":"297","author":"Davenport","year":"1982","journal-title":"Philos. Trans. R. Soc. B"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"294","DOI":"10.5670\/oceanog.2011.80","article-title":"Deepwater Horizon oil spill: A review of the planktonic response","volume":"24","author":"Abbriano","year":"2011","journal-title":"Oceanography"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1093\/biosci\/biu119","article-title":"Seaweeds and decapod crustaceans on Gulf deep banks after the Macondo Oil Spill","volume":"64","author":"Felder","year":"2014","journal-title":"Bioscience"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1648","DOI":"10.2112\/JCOASTRES-D-11-00079.1","article-title":"Fishing and tourism impacts in the aftermath of the Hebei-Spirit oil spill","volume":"28","author":"Cheong","year":"2012","journal-title":"J. Coast. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1016\/j.asr.2015.05.040","article-title":"Detection of the Hebei Spirit oil spill on SAR imagery and its temporal evolution in a coastal region of the Yellow Sea","volume":"56","author":"Kim","year":"2015","journal-title":"Adv. Space Res"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5139","DOI":"10.1109\/JSTARS.2016.2577597","article-title":"Detection and dispersion of thick and film-like oil spills in a coastal bay using satellite optical images","volume":"9","author":"Lee","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/s00244-017-0394-9","article-title":"Contamination and human health risk assessment of polycyclic aromatic hydrocarbons (PAHs) in oysters after the Wu Yi san oil spill in Korea","volume":"73","author":"Loh","year":"2017","journal-title":"Arch. Environ. Contam. Toxicol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.marpolbul.2013.05.021","article-title":"Risk assessment and national measure plan for oil and HNS spill accidents near Korea","volume":"73","author":"Lee","year":"2013","journal-title":"Mar. Pollut. Bull."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.envint.2014.05.012","article-title":"Development of a risk-based prioritisation methodology to inform public health emergency planning and preparedness in case of accidental spill at sea of hazardous and noxious substances (HNS)","volume":"72","author":"Harold","year":"2014","journal-title":"Environ. Int."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.marpolbul.2018.12.044","article-title":"Initial environmental risk assessment of hazardous and noxious substances (HNS) spill accidents to mitigate its damages","volume":"139","author":"Kim","year":"2019","journal-title":"Mar. Pollut. Bull."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"106231","DOI":"10.1016\/j.oceaneng.2019.106231","article-title":"The forecasting and analysis of oil spill drift trajectory during the Sanchi collision accident, East China Sea","volume":"187","author":"Li","year":"2019","journal-title":"Ocean Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"122978","DOI":"10.1016\/j.jclepro.2020.122978","article-title":"Marine oil spill pollution causes and governance: A case study of Sanchi tanker collision and explosion","volume":"273","author":"Chen","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3051","DOI":"10.1109\/TGRS.2017.2661325","article-title":"Multifrequency radar imagery and characterization of hazardous and noxious substances at sea","volume":"55","author":"Angelliaume","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4458","DOI":"10.1364\/AO.58.004458","article-title":"On-site visualized classification of transparent hazards and noxious substances on a water surface by multispectral techniques","volume":"58","author":"Huang","year":"2019","journal-title":"Appl. Opt."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"113688","DOI":"10.1016\/j.envpol.2019.113688","article-title":"Single spectral imagery and faster R-CNN to identify hazardous and noxious substances spills","volume":"258","author":"Huang","year":"2020","journal-title":"Environ. Pollut."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhan, S., Wang, C., Liu, S., Xia, K., Huang, H., Li, X., and Xu, R. (2019). Floating Xylene Spill Segmentation from Ultraviolet Images via Target Enhancement. Remote Sens., 11.","DOI":"10.3390\/rs11091142"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1080\/07038992.2016.1160772","article-title":"Minimum noise fraction versus principal component analysis as a preprocessing step for hyperspectral imagery denoising","volume":"42","author":"Luo","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_19","first-page":"115","article-title":"Principal component analysis for hyperspectral image classification","volume":"62","author":"Rodarmel","year":"2002","journal-title":"Surv. Land Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"248","DOI":"10.7763\/IJMLC.2012.V2.124","article-title":"Band selection for dimension reduction in hyper spectral image using integrated information gain and principal components analysis technique","volume":"2","author":"Koonsanit","year":"2012","journal-title":"Int. J. Mach. Learn. Comput."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1177\/1094342007088380","article-title":"Low-complexity principal component analysis for hyperspectral image compression","volume":"22","author":"Du","year":"2008","journal-title":"Int. J. High Perform. Comput. Appl."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1603","DOI":"10.1016\/j.rse.2011.03.003","article-title":"Endmember variability in spectral mixture analysis: A review","volume":"115","author":"Somers","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_23","unstructured":"Descour, M.R., and Shen, S.S. (1999). N-FINDR: An Algorithm for Fast Autonomous Spectral End-Member Determination in Hyperspectral Data, Imaging Spectrometry V."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/TIP.2010.2071310","article-title":"Random N-finder (N-FINDR) endmember extraction algorithms for hyperspectral imagery","volume":"20","author":"Chang","year":"2010","journal-title":"IEEE Trans. Image Process"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/LGRS.2005.856701","article-title":"A fast iterative algorithm for implementation of pixel purity index","volume":"3","author":"Chang","year":"2006","journal-title":"IEEE Geosci Remote Sens Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.1109\/TGRS.2005.863297","article-title":"Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis","volume":"44","author":"Wang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","first-page":"542","article-title":"Classification of hyperspectral images by using extended morphological attribute profiles and independent component analysis","volume":"8","author":"Villa","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2601","DOI":"10.1109\/TGRS.2006.874135","article-title":"Applications of independent component analysis in endmember extraction and abundance quantification for hyperspectral imagery","volume":"44","author":"Wang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TGRS.2005.844293","article-title":"Vertex component analysis: A fast algorithm to unmix hyperspectral data","volume":"43","author":"Nascimento","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1109\/LGRS.2011.2172771","article-title":"A low-computational-complexity algorithm for hyperspectral endmember extraction: Modified vertex component analysis","volume":"9","author":"Lopez","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1109\/36.911111","article-title":"Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery","volume":"39","author":"Heinz","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","unstructured":"Homayouni, S., and Roux, M. (2004, January 12\u201323). Hyperspectral image analysis for material mapping using spectral matching. Proceedings of the ISPRS Congress, Istanbul, Turkey."},{"key":"ref_33","first-page":"261","article-title":"Hyperspectral image classification by a variable interval spectral average and spectral curve matching combined algorithm","volume":"12","author":"Kumar","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_34","unstructured":"Sweet, J.N. (2003, January 27\u201328). The spectral similarity scale and its application to the classification of hyperspectral remote sensing data. Proceedings of the Advances in Techniques for Analysis of Remotely Sensed Data, Greenbelt, MD, USA."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1080\/07038992.2001.10854938","article-title":"Adaptive threshold for spectral matching of hyperspectral data","volume":"27","author":"Schwarz","year":"2001","journal-title":"Can. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Foucher, P.-Y., Poutier, L., D\u00e9liot, P., Puckrin, E., and Chataing, S. (2016, January 10\u201315). Hazardous and Noxious Substance detection by hyperspectral imagery for marine pollution application. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7731006"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Park, J.J., Kim, T.S., Park, K., Oh, S., Lee, M., and Foucher, P.Y. (2020). Application of Spectral Mixture Analysis to Vessel Monitoring Using Airborne Hyperspectral Data. Remote Sens., 12.","DOI":"10.3390\/rs12182968"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/B978-1-85617-943-0.10013-9","article-title":"Weather Effects on Oil Spill Countermeasures","volume":"Volume 13","author":"Fingas","year":"2011","journal-title":"Oil Spill Science and Technology"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/2\/318\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:12:35Z","timestamp":1760159555000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/2\/318"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,18]]},"references-count":38,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["rs13020318"],"URL":"https:\/\/doi.org\/10.3390\/rs13020318","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,18]]}}}