Interferometric Synthetic Aperture Radar (InSAR) can be used to detect ground motion but also processed further to generate Digital Elevation Models (DEMS). Sentinel-1 images are acquired continuously, and data is made available free of access in near real time making it a valuable tool for Earth observation and volcanic hazard assessment. Mass flow simulations require up to date DEMs for the results to be integrated in volcanic hazard management and mitigation. This study investigates the applicability of InSAR generated terrains as information and data with respect to volcanic hazard analysis as well as the input data in simulating block-and-ash flows (BAFs) following the collapse of volcanic domes on Mount Taranaki, New Zealand, using the Titan2D simulation toolkit. Results show that the accuracy of Sentinel-1 InSAR generated DEMs are limited for volcanic hazard analysis in areas of dense vegetation and steep topography due to temporal decorrelation and geometrical distortions. Together, these conditions introduce major differences in inundation extent and thickness distribution of simulated flows yet can provide some indication of flow impact which may be of relevance for rapid decision making in response to rapidly changing volcanic landscapes.

SAR amplitude change detection provides a weather-independent means of tracking volcanic deposits and associated hazards in near real-time. We use high resolution X-band COSMO SkyMed (CSK) images to generate amplitude change difference maps to identify backscatter responses to the 6th of August 2012 eruption at Upper Te Maari crater, New Zealand. This explosive eruption was hydrothermally driven and triggered by landslide induced unroofing, producing a >2 km long debris flow, ballistics and wet pyroclastic surges. Surge deposits produced both increase and decrease in amplitude, depending on pre-eruption surface cover properties. Alpine, unvegetated areas east of the crater showed a decrease in amplitude produced by surge blanketing, while rougher, vegetated areas showed an increase in amplitude when draped by wet surge material. The debris flow propagation and deposits caused significant landscape changes, marked by an increase in backscatter due to the emplacement of coarse material enhancing surface roughness. These deposits caused the damming of the Mangatipua Stream and the creation of an ephemeral lake which breached on the 15th October following heavy rainfall, remobilising sediments as a hyperconcentrated flow. We have shown that the evolution in size of the ephemeral lake can be traced using high resolution radar making it a valuable tool for hazard monitoring. Our results highlight that, in high resolution SAR data, surface roughness exerts a stronger influence on radar backscattering than soil moisture for volcanic deposits.

This review examines the current landscape of computational volcanic hazard models, focusing on their creation and application, for a diverse set of end-users’ short-term and long-term forecasting requirements. We provide a comprehensive classification of volcanic hazard models, categorising them according to their theoretical foundations. This is central to understanding the diversity of hazard characterisation and simulation approaches, from empirical models to computationally demanding physics-based numerical models. The classification framework helps contextualise the strengths and limitations of different models and their suitability for specific forecasting demands. We discuss the fundamental principles behind model construction, considering factors such as input parameters, conceptual frameworks, and the incorporation of uncertainties. We also synthesise existing literature on model testing, covering aspects such as model verification, validation, calibration, and benchmarking, and provide a systematic and transparent framework for model selection, considering data availability, computational constraints, and specific forecasting needs. We explore the balance between model complexity, computational efficiency, and accuracy, addressing the uncertainties inherent in both input parameters and model processes. A key focus is the role of input parameters in forecasting and the need to select models that are detailed enough to capture essential hazard dynamics, yet simple enough to minimise error and computational costs.

Volcanic eruptions can cause substantial damage and disruption to infrastructure and communities. Contemporary societies typically depend on petroleum infrastructure. Volcanic unrest and eruptions can cause considerable operational and structural challenges for the petroleum sector. The vulnerability of this sector to volcanic hazards is understudied when compared to other potentially dangerous phenomena (e.g. earthquakes). In this paper, we present new volcanic physical vulnerability models for the four key asset classes of the petroleum sector: wells, pipelines, production facilities and storage tanks. The vulnerability models are developed based on a literature review and facilitated expert judgement in the form of workshops with petroleum engineers and volcanic risk experts. These models consider four hazard intensity metrics (burial thickness, static load, dynamic pressure and airborne ash concentration) and are thus applicable to multiple volcanic hazards. We apply these models to pre-existing multi-hazard eruption scenarios for Taranaki Mounga volcano in Aotearoa New Zealand, using an available impact assessment framework to demonstrate their usability in impact and risk modelling. Our impact assessment indicates that a future eruption of Taranaki Mounga volcano could cause widespread impacts to the petroleum sector, which would in turn create a prolonged national emergency due to energy supply shortages for major industries and consumers. These vulnerability models may be applied in other volcanic regions worldwide to inform risk reduction and readiness actions.

Hydrothermal alteration can significantly modify the physical and mechanical properties of volcanic rocks, influencing the slope stability and eruption dynamics of andesitic volcanoes. This study presents a comparative analysis of alteration-mechanical relationships for three composite volcanoes in New Zealand: Ruapehu, Tongariro, and Whakaari. Forty rock samples representing unaltered to pervasively altered facies were characterised using reflectance spectroscopy, SEM–EDS, and laboratory measurements of porosity, permeability, elastic wave velocity, and uniaxial compressive strength (UCS). The results reveal consistent mineralogical and mechanical trends across all volcanoes: increasing alteration pervasiveness is generally associated with decreasing strength and permeability, except for silicic alteration, which locally strengthens rocks through silica cementation. Intermediate argillic alteration exhibits the greatest variability in both mineralogy and mechanical behaviour, reflecting the complex interplay between dissolution and precipitation processes. Despite differences in hydrothermal system dynamics and volcanic architecture, alteration facies exert similar controls on rock properties across all sites, suggesting globally transferable relationships. These findings enable the development of a unified conceptual model linking hydrothermal alteration, rock physical and mechanical properties, and volcanic hazard potential, which can improve numerical models of edifice stability and enhance remote sensing–based hazard assessments.

This study characterizes the amplitude changes associated with the 4 December 2021 eruption of Mount Semeru and maps the resulting deposits using Sentinel-1 SAR backscatter and PlanetScope optical imagery. Results show that lahar deposits caused surface smoothening which reduced SAR backscatter, whereas pyroclastic density currents (PDCs) increased backscatter due to higher moisture content. We have also shown the potential of differential polarimetric responses between surface cover types to identify areas of channel widening and vegetation destruction, providing a rapid means of identifying impacted areas in the context of volcanic crisis management. The supervised classification of SAR and high-resolution optical images enabled the production of an accurate geomorphological map able to separate different pyroclastic flow and lahar flow deposits both sedimentologically and spatially. Classified channelized lahar deposits were also used to quantify channel widening associated with the eruption, which significantly impacted the Supiturang Village.

Volcanoes are dynamic and complex natural systems, constantly changing through eruptions, alteration, and erosion. Hydrothermal systems are ubiquitous on volcanoes, causing physical and mechanical change to rock properties via hydrothermal alteration. The most commonly measured rock physical properties are porosity and uniaxial compressive strength (UCS) as they provide insight as to their history and potential mechanical behavior. Porosity and UCS are affected by the primary properties and emplacement history (e.g., volatile content, crystallinity, cooling rate, composition, fragmentation type) and the post-emplacement conditions (e.g., surface weathering and hydrothermal alteration). This creates highly heterogenous rock masses, with variation occurring across mm to m scales. Currently, destructive testing is required to measure UCS and porosity (destructive of the wider sample) accurately and needs a large volume of samples to capture the heterogeneity of volcanic rock masses. This testing is cost and time prohibitive, requiring large sample volume, in terms of sample size and number, which often require shipping to specialist labs. Schmidt hammers can be used to estimate UCS non-destructively, however, they produce inaccurate results on soft rocks such as hydrothermally altered rocks. Here, we present a new non-destructive method for predicting porosity and UCS across a range of volcanic rocks, from non-altered to highly altered. This study uses visible-near infrared (VNIR) to shortwave infrared (SWIR) wavelengths (350-2500 nm) reflectance spectroscopy to predict porosity and UCS via Partial Least Squares Regression (PLSR). Reflectance spectroscopy is a non-destructive method that is sensitive to both physical (surface roughness and crystal/particle size) and chemical (mineral species and abundance) properties of volcanic rocks. Because these rock attributes also influence the physical and mechanical properties of rock, reflectance spectroscopy could be used to quantitatively predict porosity and UCS. This study used experimentally deformed volcanic rocks from Ruapehu, Ohakuri, Whakaari, and Banks Peninsula (New Zealand), Merapi (Indonesia), Chaos Crags (USA), Styrian Basin (Austria), La Soufrière de Guadeloupe (Eastern Caribbean), Volvic (France), and Cracked Mountain (Canada) to evaluate the accuracy of PLSR-based predictions for porosity and UCS. The training samples encompass a wide range of volcanoes, alteration degree (non-altered, silicic, argillic, and phyllic alteration), mineralogical differences (initial composition from basalt to rhyolite and alteration products), and textural differences (original textures such as lava and pyroclastic, and alteration textures including veins). Model sensitivity is evaluated by adding randomly individual samples to the training database or performing leave one group out cross validation based on characteristics (e.g., alteration mineral types, textural features, or volcano location). From this analysis, specific alteration mineralogy can be evaluated for its effect on porosity and UCS predictions such as the role of phyllosilicate formation causing a reduction in UCS. The proposed non-destructive method via VNIR-SWIR spectroscopy can complement existing rock mechanical testing methods to better quantify highly heterogenous volcanic and hydrothermal systems and their rock successions.

Depressurisation from edifice collapse events can impact the subvolcanic plumbing system as a propagation wave moves down through the system shifting the fragmentation zone. Understanding how this influences the eruptive behaviour at a volcano is important for understanding changes in hazards following a large edifice collapse event. Mt. Taranaki has experienced at least 16 collapse events within its > 200 kyr history. Two of the largest collapse events the 27.3 ka Ngaere and 24.8 ka Pungarehu debris avalanches occurred in close succession and were encompassed by the Poto and Paetahi tephra formations, made up of 28 subplinian eruptions over ~ 4,000 years. This eruptive period provides a unique opportunity to examine and understand the influence that edifice collapse events have on the subvolcanic plumbing system. Using 3D Micro-Computed Tomography at the Australian Synchrotron bubble textural analysis was undertaken to investigate the changes in pyroclastic textures from large explosive eruptions and how these change following an edifice collapse event. The high-resolution 3D scans indicate that the eruptive products from the Poto and Paetahi Formations are dominated by small bubbles (2.7 x 10-7 mm3) with high bubble number densities ranging from 2.56 x 1015 cm-3 to 1.74 x 1016 cm-3. Bubble size distributions for the Poto and Paetahi Formations indicate a range of bubble nucleation and growth processes occurring within the subvolcanic plumbing system below Mt. Taranaki initiating at different depths. Early onset of bubble nucleation and periods of magma stalling are indicated by the presence of large, coalesced bubbles within the eruptive products, while the dominance of smaller bubbles indicates a fast ascent of magma within the system with nucleation occurring higher up in the system. Changes are seen in the textural characteristics of pyroclasts produced following the 27.3 ka 5.85 km3 Ngaere collapse which depressurized the shallow magmatic system and shifted the fragmentation zone. Following the 24.8 ka 7.5 km3 Pungarehu collapse ~2,500 years later the same influence is not seen, due to the cone not having enough time to rebuild between edifice collapse events. The results from this study show that the depressurisation and subsequent propagation wave are dependent on the height above the plumbing system not just the mass removed and therefore two major collapses in close proximity do not show the same systematic impact on the fragmentation zone.

Volcanic ash is a widespread and destructive volcanic hazard. Timely and accurate forecasts for ash deposition and dispersal help mitigate the risks of volcanic hazards to society. Producing these forecasts requires numerous simulations with varying input parameters to encapsulate uncertainty and accurately capture the actual event to deliver a reliable forecast. However, exploring all possible combinations of input parameters is computationally infeasible in the lead up to an eruption. This research explores the input space of two volcanic ash transport and dispersion models, Tephra2, which is based on a simplified analytical solution, and Fall3D, which is a computational model based on more general assumptions, in the context of forecasting an unknown future eruption. We use the exemplar of Taranaki Mounga (Mount Taranaki), Aotearoa New Zealand, which has an estimated 30% to 50% chance of an explosive eruption in the next 50 years. We statistically determine how much each input parameter contributes to model output variance through a global sensitivity analysis via Sobol' indices and the extended Fourier Amplitude Sensitivity Test (eFAST). Our findings show that grain size distribution, diffusion, plume shape, and plume duration (Fall3D only) have a substantial first-order impact on model output variance. In contrast, mass, particle density, and plume height have minimal impact in the first-order but become influential when considering parameter-parameter inter-relationships (total-order). The results not only enhance our understanding of model sensitivities but also point to improved efficiency in forecasting efforts.

The sudden removal of large portions of a volcanic edifice through collapse can cause depressurisation in the subvolcanic magmatic system, influencing the nature of subsequent eruptions. At Mt. Taranaki, edifice failure has occurred frequently and at different timescales throughout the volcanic history, forming a broad pattern of cyclic collapse and regrowth. About 20-30,000 years ago, Mt. Taranaki experienced two such cycles in short succession, emplacing the 27.3 ka Ngaere and the 24.8 ka Pungarehu debris-avalanche deposits, which were preceded and followed by a sequence of twenty-eight closely spaced tephra deposits known as the Poto and Paetahi Formations. Here, we reconstruct the tephrastratigraphic framework of the Poto and Paetahi Formations, revealing a minimum total eruptive volume of 3 km3. While eruptions directly following edifice failure were larger compared to those prior to collapse, this 4,000-year long eruptive period was characterised by consistently large subplinian eruptions. In contrast, large explosive events within the Holocene sequence are less frequent, with more multi-phase periods of effusive and explosive activity recorded. Our new data highlights the need to include longer-term eruptive records in volcanic hazard modelling since the most recent volcanic history might not cover the full nature of volcanic processes occurring at long-lived stratovolcanoes.

Volcanic communities near long-lived stratovolcanoes are susceptible to the significant threat associated with edifice collapse events which produce volcanic debris avalanches. These events can have runout distances > 100 km and are the largest mass flows on Earth with volumes ranging from 0.1 to 100 km3 which have the potential to bury large sectors of the landscape posing a severe risk to people and infrastructure. However, the emplacement mechanisms of these large destructive phenomena are still poorly understood with the inability to accurately quantify the physical parameters such as frictional regimes, velocity, and temperature which contribute to the extreme runout. The internal structure and minerology of the avalanche deposits hold the key to understanding the transportation mechanisms. During transportation inter-particle collision and shearing occurs reducing grainsize and generating new minerals such as Pseudotachylytes, Frictionites and Silica polymorphs along shear zones between larger clasts and along the base of the flow. Twenty-five volcanic debris avalanches and rock avalanches of varying sizes were sampled from New Zealand and the USA to provide a representative variety of flow types to better understand transportation mechanisms. Using 3D Micro-Computed Tomography at the Australian Synchrotron the internal structure of the avalanche deposits were analysed to identify different minerals and structures present. Analysis of the microstructures of the samples show a variety of different fracture patterns that can be categorized based on the different source lithologies sampled as well as the different rheological emplacement conditions from the collapse and flow. Features seen at the micro-scale mimic larger centimeter to meter scale features traditionally observed in the flow. Investigating the formation of new minerals along collision and shear zones can provide insights on the physical constraints of the flow e.g., velocity and temperature. Data from this study will provide quantitative input parameters forming the foundation for developing a model for transportation and emplacement of long-runout volcanic debris avalanches. Data from these models can be used to assess the volcanic debris avalanche hazards from volcanoes globally, better informing risk assessments.

Accurate forecasts are needed to help mitigate the risks of volcanic hazards to society. Current approaches use probabilistic estimates based on sparse data, supplemented with expert judgment, to describe likely future eruption characteristics. These probabilistic eruption characteristics then inform input parameters required by hazard models. This process requires a lot of simulations with varying input parameters to constrain uncertainty around a future eruption’s hazard characteristics. It is also computationally intensive, and the outputs may quantify, but do not reduce eruption uncertainty. As hazard models become increasingly more complex, so do the number of input parameters that need to be estimated, thus increasing the number of sources of uncertainty. As input parameters used for volcanic hazard models are fundamentally uncertain before (and often also after) an eruption, how do they affect the accuracy and utility of forecasts made using these models? This research explores the input space of volcanic hazard models to understand the interactions between model complexity and robustness of hazard model forecasts. We use the exemplar of volcanic ash distribution models Tephra2 and Fall3D at Mt. Taranaki, Aotearoa-New Zealand (30-50% chance of eruption in the next 50 years). Sampling strategies for Tephra2 and Fall3D were developed to ensure that the input parameter space was fully covered and represent real-world values – both through independent and dependent sampling of parameters. For example, plume height is dependent on the amount of mass ejected during an eruption. A Global Sensitivity Analysis is presented here to investigate the input parameters that significantly influence model output variance. This exploration is conducted through the statistical assessment of Sobol’ indices and eFAST (extended Fourier Amplitude Sensitivity Tests) to discern the key parameters that contribute to variations in the model’s outputs. The results also shed light on which inputs are vital to robust short-term and real-time hazard forecasting, and ultimately require better understanding/quantification before an event.

Radar interferometry can be used to detect ground motion but also further processed to generate Digital Elevation Models (DEMS). Sentinel-1 images are acquired continuously, and data is made available free of access in near real time making it a valuable tool for Earth observation and hazard assessment. Interferometric radar requires strong coherence between pairs of images used to be able to generate accurate results. This study on Mount Taranaki, New Zealand shows that the accuracy of InSAR generated DEMs is of limited potential in areas of dense vegetation and steep topography due to temporal decorrelation and geometrical distortions.

Small-to-moderate explosive eruptions involve VEIs ≤ 3, tephra volumes ≤ 0.1 km3 and often eject a significant amount of ash-sized pyroclastic material. This reduces the preservation potential of associated deposits and leads to an underrepresentation of these low- to mid-intensity explosive eruptions in long-term, frequency-magnitude datasets. Mt. Ruapehu is one of New Zealand’s most active volcanoes, having produced at least 32 small-to-moderate eruptions over the past 1800 years. The largest of these eruptions deposited the widespread T13-sequence and lasted several months to years. The cumulative deposit volume is estimated at 0.15 km3, thus being an order of magnitude larger than the average deposit volumes of the last 1800 years at Ruapehu. The sequence of pyroclastic fall deposits can be subdivided into six depositional sub-units representing at least five eruption phases of variable intensity and magnitude. The ash-lapilli sequence displays variable dispersal, deposit textures and pyroclast characteristics. While the initial phase is characterised by dispersal limited to the proximal 11 km and a tephra volume of 8.5 × 105 m3 (± 3

All historical eruptions at Ruapehu have occurred from its Crater Lake, Te Wai ā-moe. This study aims to better understand Crater Lake dynamics by using visible light and long wavelength infrared images of the lake. Over 10,000 images from 1902 – 2021 were analysed to produce a time-series of lake observations. Our results show that visible light observations reveal colour changes on the entire Crater Lake surface from blue to grey, and localised grey, yellow, and black discolourations. Grey discolourations are interpreted as localised upwellings of lake-floor sediment, and yellow and black material to comprise vent-hosted sulphur/sulphides, both transported by volcanic fluids from subaqueous vents to the surface. The locations of upwellings were used to identify five vent locations beneath Crater Lake, three more vents than were previously recognised. Upwellings appeared and disappeared in 10 min. Steam above the lake surface was controlled by both lake temperature and cloud conditions. Blue lakes were most common in summer and autumn, implying a relationship with ice or snow melt entering the lake. Grey lakes were observed in the month before 97

Detailed stratigraphic reconstructions and quantitative deposit characterisations of moderate to large-scale rhyolitic eruptions are limited. This hinders our ability to model the multiple eruptive phenomena and hazards associated with rhyolitic volcanism. To gain new perspectives on the patterns and behaviours of rhyolitic eruptions, we present a study on the explosive phases of the 1314 +/- 12 CE Kaharoa eruption of Tarawera, New Zealand. The eruption occurred from multiple aligned vents within the Okataina Caldera and is the youngest rhyolitic eruption of the frequently active Taupo Volcanic Zone. We systematically quantify the deposit characteristics of the Kaharoa pyroclastic succession to provide new insights into the type of eruption sequence and eruptive style changes. Based on field evidence, stratigraphic correlations, grain size and componentry analyses, we subdivide the Kaharoa deposit into 24 units and identify 7 main deposit types, which are linked to different eruptive and depositional processes. The explosive activity was discontinuous, characterised by repeated discrete episodes of sustained magma discharge separated by short time breaks. The activity consisted mainly of repeated subplinian-type columns that gave way to fallout deposition and emplacement of numerous lapilli beds. This activity transitioned to a pyroclastic density current (PDC) dominated phase in response to lateral vent migration. Ash emission activity occurred within and towards the end of the explosive sequence, indicating declines in the eruptive intensity. Six main intra-eruption phases (A to F) of dominant eruptive styles are established to describe the temporal evolution of the eruption. Phases A, B and D are associated with the repeated subplinian-type activity. Phase C comprises the major PDC activity, while the final two Phases E and F are associated with ash emission during initiation of lava dome extrusion and to the final dome-building sequence. This study highlights the complex nature of episodic, multi-phase, and multi-vent, explosive to dome-forming rhyolitic eruptions, depicting a scenario of great relevance for future volcanic hazard studies at active rhyolitic volcanoes worldwide.

To establish if highly eutrophic lakes generate higher N2O emissions than non-eutrophic aquatic environments in New Zealand, we monitored N2O emissions from hypereutrophic Lake Horowhenua, near Levin, and the oligotrophic Turitea dam reservoir, near Palmerston North, used as control. Based on more than 12 months of monitoring data, N2O emissions from Lake Horowhenua were estimated to -0.05-6.93 mg-N2Om(-2)d(-1) (n = 66), with a median of 0.30 mg-N2Om(-2)d(-1). At the Turitea reservoir, N2O emissions ranged from -0.02-1.51 mg-N2Om(-2)d(-1) with a median of 0.15 mg-N2Om(-2)d(-1) (n = 53). No correlation was found between N2O emissions and the water temperature, sunlight, dissolved oxygen, nutrient concentration or chlorophyll a. When extrapolating the emission data to NZ, we estimated NZ lakes could release 83 kt of N2O as CO(2)eq each year, which is low in comparison to other sectors such as agriculture. Following the Intergovernmental Panel on Climate Change methodology, the N2O emission factor for Lake Horowhenua was estimated at 0.0019 kg N2O-N per kg of N-NO3- input into the lake.

Probabilistic volcanic hazard assessments require (1) an identification of the hazardous volcanic source; (2) estimation of the magnitude-frequency relationship for the volcanic process; (3) quantification of the dependence of hazard on magnitude and external conditions; and (4) estimation of hazard exceedance from the magnitude-frequency and hazard intensity relationship. For volcanic mass flows, quantification of the hazard is typically undertaken through the use of computationally expensive mass flow simulators. However, this computational expense restricts the number of samples that can be used to produce a probabilistic assessment and limits the ability to rapidly update hazard assessments in response to changing source probabilities. We develop an alternate approach to defining hazard intensity through a surrogate model that provides a continuous estimate of simulation outputs at negligible computational expense, demonstrated through a probabilistic hazard assessment of dome collapse (block-and-ash) flows at Taranaki volcano, New Zealand. A Gaussian Process emulator trained on a database of simulations is used as the surrogate model of hazard intensity across the input space of possible dome collapse volumes and configurations, which is then sampled using a volume-frequency relationship of dome collapse flows. The demonstrated technique is a tractable solution to the problem of probabilistic volcanic hazard assessment, with the surrogates providing a good approximation of the simulator, and is generally applicable to volcanic hazard and geo-hazard assessments that are limited by the demands of numerical simulations and changing source probabilities.

ABSTRACT Many stratovolcanoes are characterised by cycles of edifice growth interrupted by collapse events. The long-term record of the evolution of such magmatic systems is mainly preserved in the deposits of the volcanic apron surrounding the active cone. Taranaki Volcano in New Zealand provides an unusually detailed example of these processes due to excellent coastal ring-plain and young cone exposures. In this study, we investigate the magmatic system of this volcano through three consecutive growth phases by sampling a detailed, stratigraphically controlled selection of volcanic clasts from volcaniclastic mass-flow deposits in the medial ring-plain. The clasts from three growth phases (GP1, 65–55 ka; GP2, 55–40 ka; GP3, 40–34 ka) differ in bulk composition and form geochemically distinct trends on variation diagrams. These trends can be modelled by mainly dacitic melt mixing with gabbroic and ultramafic xenolith compositions representing the plutonic assemblages beneath the edifice. Within short-term growth cycles (104 years), the geochemical differences between lower and upper sequences of GP units indicate that closer to an edifice collapse, both whole-rock major and trace element compositions display more evolved and scattered trends compared to post-collapse stages. Considering the long-term magmatic evolution of Taranaki Volcano, it is apparent that the pre-collapse compositions are more evolved than bulk rock compositions of the growth phases, indicating active upper-crustal reservoir conditions in pre-collapse states. Furthermore, the volume losses caused by sector collapses prior to GP2 and GP3 could decrease the pressure in the upper-crustal reservoir. Overall, the data obtained from the mid-age Taranaki volcanic system elucidate the mid- to upper-crustal magmatic processes and reservoir conditions throughout growth cycles. Further, it demonstrates the top-down control of volcanic edifice load change on the magmatic plumbing system expressed by the evolvement of whole-rock compositions towards the end of a growth cycle.

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.