Hyperspectral remote sensing in lithological mapping, mineral exploration, and environmental geology: an updated review

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dc.contributor.authorPeyghambari, Sima
dc.contributor.authorZhang, Yun
dc.date.accessioned2023-06-07T11:56:38Z
dc.date.available2023-06-07T11:56:38Z
dc.date.issued2021
dc.description.abstractHyperspectral imaging has been used in a variety of geological applications since its advent in the 1970s. In the last few decades, different techniques have been developed by geologists to analyze hyperspectral data in order to quantitatively extract geological information from the high-spectral-resolution remote sensing images. We attempt to review and update various steps of the techniques used in geological information extraction, such as lithological and mineralogical mapping, ore exploration, and environmental geology. The steps include atmospheric correction, dimensionality processing, endmember extraction, and image classification. It is identified that per-pixel and subpixel image classifiers can generate accurate alteration mineral maps. Producing geological maps of different surface materials including minerals and rocks is one of the most important geological applications. The hyperspectral images classification methods demonstrate the potential for being used as a main tool in the mining industry and environmental geology. To exemplify the potential, we also include a few case studies of different geological applications.
dc.description.copyright© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. https://doi.org/10.1117/1.JRS.15.031501
dc.identifier.doi10.1117/1.jrs.15.031501
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/29872
dc.language.isoen
dc.publisherSociety of Photo-optical Instrumentation Engineers
dc.relationCanadian Space Agency
dc.relation.hasversionhttps://doi.org/10.1117/1.JRS.15.031501
dc.relation.ispartofJournal of Applied Remote Sensing
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineGeodesy and Geomatics Engineering
dc.titleHyperspectral remote sensing in lithological mapping, mineral exploration, and environmental geology: an updated review
dc.typejournal-article
oaire.citation.issue3
oaire.citation.titleJournal of Applied Remote Sensing
oaire.citation.volume15
oaire.license.conditionhttp://creativecommons.org/licenses/by/4.0/
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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