Browsing by Author "Rodriguez-Gomez C"

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    Integrating petrology, biogeochemistry, hyperspectral and thermal remote sensing for constraining the shallow hydrology of geothermal systems: Waiotapu Geothermal Field, Taupo Volcanic Zone, New Zealand
    (Taylor and Francis Group on behalf of The Royal Society of New Zealand, 2024-06-12) Rodriguez-Gomez C; Kereszturi G; Reeves R; Rae A; Palmer M
    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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    Probabilistic Volcanic Hazard Assessment for National Park Infrastructure Proximal to Taranaki Volcano (New Zealand)
    (Frontiers Media S.A., 2022-03-28) Mead S; Procter J; Bebbington M; Rodriguez-Gomez C; Fontijn K
    Hazard assessment for infrastructure proximal to a volcanic vent raises issues that are often not present, or not as severe in hazard assessments for more distal infrastructure. Proximal regions are subject to a greater number of hazardous phenomena, and variability in impact intensity increases with the hazard magnitude. To probabilistically quantify volcanic hazard to infrastructure, multiple volcanic hazards and their effects on exposed elements need to be considered. Compared to single-hazard assessments, multi-hazard assessments increase the size and complexity of determining hazard occurrence and magnitude, typically introducing additional uncertainties in the quantification of risk. A location-centred approach, focusing on key locations rather than key hazards, can simplify the problem to one requiring identification of hazards with the potential to affect the location, followed by assessment of the probability of these hazards and their triggering eruptions. The location-centred approach is more compatible to multi-source hazards and allows for different hazard estimation methodologies to be applied as appropriate for the infrastructure type. We present a probabilistic quantification of volcanic hazard using this location centred approach for infrastructure within Te Papakura o Taranaki National Park, New Zealand. The impact to proposed park infrastructure from volcanic activity (originating from Mt. Taranaki) is quantified using a probability chain to provide a structured approach to integrate differing hazard estimation methods with eruption probability estimates within asset lifetimes. This location-centered approach provides quantitative estimates for volcanic hazards that significantly improve volcanic hazard estimates for infrastructure proximal to the Taranaki summit vent. Volcanic mass flows, predominantly pyroclastic surges or block and ash flows, are most likely (probability >0.8) to affect walking tracks if an eruption occurs. The probability of one or more eruption(s) in the next 50 years is estimated at 0.35–0.38. This use of probability chains and a location centered assessment demonstrates a technique that can be applied to proximal hazard assessments globally.
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    Remote exploration and monitoring of geothermal sources: A novel method for foliar element mapping using hyperspectral (VNIR-SWIR) remote sensing
    (Elsevier Ltd, 2023-06) Rodriguez-Gomez C; Kereszturi G; Jeyakumar P; Pullanagari R; Reeves R; Rae A; Procter JN
    Hyperspectral remote sensing is an emerging technique to develop new cost- and time-effective geophysical mapping methods. To overcome challenges introduced by plant cover in geothermal systems globally, we hypothesise that foliage can be used as a proxy to map underlying surface geothermal activity and heat-flux due to their capability on elemental uptake from geothermal fluids and host rock/soil. This study shows for the first time that foliar elemental mapping can be used to image geothermal systems using both high-resolution airborne and satellite hyperspectral images. This study has specifically targeted kanuka shrub (kunzea ericoides var. microflora) as a proxy media to develop air- and spaceborne hyperspectral solutions to monitor inaccessible, biologically and culturally sensitive geothermal areas. Using high resolution airborne AisaFENIX and PRISMA hyperspectral data, foliar element maps for Ag, As, Ba and Sb have been developed using Kernel Partial Least Squares Regression and Random Forest classification models to track their foliar distribution and develop a conceptual model for metal and thermal induced changes in plants. Our study shows evidence that the created foliar element maps are in concordance with independent LiDAR-retrieved canopy structure and height as well as temperature effects of the underlying geothermal field. This study has proven air- and spaceborne hyperspectral sensors can indeed capture critical information within the VNIR and SWIR regions (e.g. ∼452, ∼500, ∼670, ∼820, ∼970, ∼1180, ∼1400 and ∼2000 nm) that can be used to identify metal and thermal-induced spectral changes in plants reliably (overall accuracy of 0.41–0.66) with remotely sensed imagery. Our non-invasive method using hyperspectral remote sensing can complement existing practices for exploration and management of renewable geothermal resources through timely monitoring from air- and spaceborne platforms.