Inferring arsenic anomalies indirectly using airborne hyperspectral imaging – Implication for gold prospecting along the Rise and Shine Shear Zone in New Zealand

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dc.citation.volume263
dc.contributor.authorChakraborty R
dc.contributor.authorKereszturi G
dc.contributor.authorPullanagari R
dc.contributor.authorCraw D
dc.contributor.authorDurance P
dc.contributor.authorAshraf S
dc.date.accessioned2024-11-24T21:48:27Z
dc.date.available2024-11-24T21:48:27Z
dc.date.issued2024-08-01
dc.description.abstractWell-exposed mineral deposits are scarce at a global level and presently potential mineral-rich sites are underlying vegetation cover and topsoil, which are suboptimal for direct remote sensing based exploration techniques. This study aims to implement an indirect approach to arsenic (As) distribution mapping using the surface manifestations of the subsurface geology and link it to the known gold mineralisation in the study area. Rise and Shine Shear Zone (RSSZ) in New Zealand is broadly a part of the Otago schist hosting lower to upper green-schist facies rocks manifesting mesothermal gold mineralisation. The area has several surficial geological imprints separating mineralised and non-mineralised zones, but these are dominated by topographic ruggedness, soil moisture and vegetation (mainly grass/tussock) spectra in the hyperspectral data. Initially, a band selection using Recursive Feature Elimination (RFE) was executed. The bands generated were tallied with the field and geological understanding of the area. The resultant 85 bands were then further put through Orthogonal Total Variation Component Analysis (OTVCA) to concise the information in 10 bands. OTVCA output was then classified using Random Forest classifier to map three levels of As concentration (<20 ppm, between 20 and 100 ppm and >100 ppm). The potentially high As concentration zones are likely to be related to the gold mineralisation. The geology of the area correlates with soil exposure which is captured by the classification in some parts, this increases the accuracy but also makes the classification analysis challenging.
dc.description.confidentialfalse
dc.edition.editionAugust 2024
dc.identifier.citationChakraborty R, Kereszturi G, Pullanagari R, Craw D, Durance P, Ashraf S. (2024). Inferring arsenic anomalies indirectly using airborne hyperspectral imaging – Implication for gold prospecting along the Rise and Shine Shear Zone in New Zealand. Journal of Geochemical Exploration. 263.
dc.identifier.doi10.1016/j.gexplo.2024.107510
dc.identifier.eissn1879-1689
dc.identifier.elements-typejournal-article
dc.identifier.issn0375-6742
dc.identifier.number107510
dc.identifier.piiS0375674224001262
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/72066
dc.languageEnglish
dc.publisherElsevier B V
dc.publisher.urihttps://www.sciencedirect.com/science/article/pii/S0375674224001262
dc.relation.isPartOfJournal of Geochemical Exploration
dc.rights(c) 2024 The Author/s
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectHyperspectral imaging
dc.subjectBand selection
dc.subjectOTVCA
dc.subjectGold mineralisation
dc.subjectArsenic
dc.subjectClassification
dc.titleInferring arsenic anomalies indirectly using airborne hyperspectral imaging – Implication for gold prospecting along the Rise and Shine Shear Zone in New Zealand
dc.typeJournal article
pubs.elements-id489017
pubs.organisational-groupOther
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