Prospectivity mapping for high sulfidation epithermal porphyry deposits using an integrated compositional and topographic remote sensing dataset

Journal article


Ganas, Athanassios, Pope, Richard and Ferrier, Graham 2019. Prospectivity mapping for high sulfidation epithermal porphyry deposits using an integrated compositional and topographic remote sensing dataset. Ore Geology Reviews. 107, pp. 353-363. https://doi.org/10.1016/j.oregeorev.2019.02.029
AuthorsGanas, Athanassios, Pope, Richard and Ferrier, Graham
Abstract

The targeting and discovery of epithermal porphyry mineral deposits can be enhanced using a structured quantitative methodology to analyse the distribution of ore deposits and model their spatial association with exploration evidence providing improved understanding on the controls of ore deposition. A novel exploration tool integrating field and ASTER SWIR and TIR satellite imagery has been developed which provides an enhanced means of resolving surface expressions of the residual silica core of the lithocap. The alteration zones were clearly resolved by the remote sensing data and an intimate spatial relationship between high-grade altered rocks and topographic highs was identified at a number of locations. A Mineral Prospectivity Modelling (MPM) approach, parameterized by the results of the remote sensing study, using a GIS-based weighted linear combination implementation of a Multi-Criteria Evaluation approach and utilising a fuzzy Analytical Hierarchy Process to elucidate expert knowledge has been implemented to target high sulfidation epithermal porphyry deposits on the Island of Lesvos, Greece. The results from this integrated altitudinal-compositional modelling approach closely matched the hydrothermal alteration mapped in the field supporting the accuracy of this MPM approach.

KeywordsProspectivity mapping sulfidation epithermal porphyry deposits integrated compositional and topographic remote sensing dataset
Year2019
JournalOre Geology Reviews
Journal citation107, pp. 353-363
PublisherElsevier
ISSN01691368
Digital Object Identifier (DOI)https://doi.org/10.1016/j.oregeorev.2019.02.029
Web address (URL)http://hdl.handle.net/10545/623675
hdl:10545/623675
Publication dates26 Feb 2019
Publication process dates
Deposited17 Apr 2019, 11:33
Accepted25 Feb 2019
ContributorsUniversity of Hull, National Observatory of Athens and University of Derby
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