Mineral prospecting via biogeochemical signals and surface indicators using hyperspectral remote sensing : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Earth Science at Massey University, Palmerston North, New Zealand

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Preliminary steps of mineral exploration have traditionally included drilling and other destructive, expensive, and time-consuming techniques. To meet the ever-increasing demand for mineral resources pertaining to the increase in population and technological demand, it is very important to develop environmentally friendly, faster, and cheaper prospecting methods. In this study, we have targeted three known regions of mesothermal gold mineralisation in the South Island, New Zealand to develop hyperspectral remote sensing-based prospect models combined with biogeochemical data. The three study sites have geological similarities around the gold mineralisation including the major pathfinder elements. On the contrary the environmental settings, and other surficial and near-surface processes including the soil and groundwater interactions with the host rock, are vastly different. This led to a wide variation in the physico-chemical properties of the soil cover and the subsequent uptake by the overlying vegetation. The Pinus radiata plantation at the Hyde-Macraes Shear Zone was the first study site to test the feasibility of using biogeochemical responses overlying the gold mineralisation through hyperspectral remote sensing for gold prospecting. Pinus radiata is known to be an accumulator of metals and metalloids with roots reaching as deep as the shear zone beneath it. The data showed a good spatial elemental trend along the shear zone for both the bark and the needle samples although the regression models performed much better with R2CV >0.7 for the bark samples. After confirming the feasibility of utilising the vegetation cover as a medium, the second site in the Rise and Shine Shear Zone was examined to assess the limits of the airborne hyperspectral data over variably exposed soil. The potentially high As anomalies indicating the gold mineralisation were classified coupled with a thorough understanding of the soil cover and its relation to the lithology. The orthogonal total variation component analysis transformed data produced the best-performing models using random forest classification with an accuracy ~50% for the high concentration As zonation. Finally, the third study site in Reefton exhibited a multi-species natural forest overlying the gold mineralisation. Apart from varying elemental responses among the different species the Reefton study area also manifested regions contaminated by previous mining activity which likely impacted the elemental uptake in the overlying vegetation. The regression models performed poorly but the spatial predictions rendered some valid correlations based on ground knowledge from previous studies.
Listed in 2023 Dean's List of Exceptional Theses
Biogeochemical prospecting, Gold, Remote sensing, Multispectral imaging, New Zealand, South Island, Image processing, Dean's List of Exceptional Theses