Abstract

ABSTRACT Studying geothermal areas can require significant resources, especially in areas densely covered by vegetation. This study integrates remote sensing techniques, including hyperspectral, thermal infrared and LiDAR with petrology and biogeochemistry of rock, soil and plant samples to develop a new shallow hydrogeological conceptual model of Waiotapu Geothermal Field, New Zealand. Previous studies present in detail each technique converging in this comprehensive research work. This geothermal area is densely covered by kanuka, an endemic shrub species to geothermal areas of New Zealand. Kanuka served as a key component in generating foliar element zonation maps for antimony and barium, utilising random forest classification validated by leave-one-out cross-validation. Thermal infrared data were employed to assess the behaviour of thermal anomalies through point pattern analysis. Results identified two intermingling processes within the single system: one in the north characterised by acid-sulphate alteration, bioavailability of barium to kanuka, and clustered surface thermal anomalies; another in the south where elements like silver, arsenic, and antimony are bioavailable to kanuka, accompanied by chloride-rich waters and denser yet non-clustered surface thermal anomalies. These cohesive methodology illustrates the efficacy of remote sensing techniques, showcasing the effectiveness of remote sensing in evaluating vegetated areas for geothermal exploration potential.

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