Massey Research Online - Browsing by Author "Kereszturi G"

Browsing by Author "Kereszturi G"

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A physically informed multi-scale deep neural network for estimating foliar nitrogen concentration in vegetation
(Elsevier B.V., 2024-05-28) Dehghan-Shoar MH; Kereszturi G; Pullanagari RR; Orsi AA; Yule IJ; Hanly J
This study introduces a Physically Informed Deep Neural Network (PINN) that leverages spectral data and Radiative Transfer Model insights to improve nitrogen concentration estimation in vegetation, addressing the complexities of physical processes. Utilizing a comprehensive spectroscopy dataset from various species across dry/ground (n = 2010), leaf (n = 1512), and canopy (n = 6007) scales, the study identifies 13 spectral bands key for chlorophyll and protein quantification. Key bands at 2276 nm, 755 nm, 1526 nm, 2243 nm, and 734 nm emerged vital for accurate N% prediction. The PINN outperforms partial least squares regression and standard deep neural networks, achieving an R2 of 0.71 and an RMSE of 0.42 (%N) on an independent validation set. Results indicate dry/ground data performed best (R2 = 0.9, RMSE = 0.24 %N), with leaf and canopy data showing lower efficacy (R2 = 0.67, RMSE = 0.45 %N; R2 = 0.65, RMSE = 0.46 %N, respectively). This multi-scale approach provides insights into spectral and N% relationships, enabling precise estimation across vegetation types and facilitating the development of transferable models. The PINN offers a new avenue for analyzing remote sensing data, demonstrating the significant potential for accurate, scale-spanning N% estimation in vegetation. Further enriching our analysis, the inclusion of seasonal data significantly enhanced our model's performance in field spectroscopy, with notable improvements observed across summer, spring, autumn, and winter. This adjustment underlines the model's increased accuracy and predictive capability at the field spectroscopy scale, emphasizing the vital role of integrating environmental factors, including climatic and physiological aspects, in future research.
A Unified Physically Based Method for Monitoring Grassland Nitrogen Concentration with Landsat 7, Landsat 8, and Sentinel-2 Satellite Data
(MDPI (Basel, Switzerland), 2023-05-09) Dehghan-Shoar MH; Pullanagari RR; Kereszturi G; Orsi AA; Yule IJ; Hanly J; Berger K; Croft H; Liu T; Lu B; Yin D
The increasing number of satellite missions provides vast opportunities for continuous vegetation monitoring, crucial for precision agriculture and environmental sustainability. However, accurately estimating vegetation traits, such as nitrogen concentration (N%), from Landsat 7 (L7), Landsat 8 (L8), and Sentinel-2 (S2) satellite data is challenging due to the diverse sensor configurations and complex atmospheric interactions. To address these limitations, we developed a unified and physically based method that combines a soil–plant–atmosphere radiative transfer (SPART) model with the bottom-of-atmosphere (BOA) spectral bidirectional reflectance distribution function. This approach enables us to assess the effect of rugged terrain, viewing angles, and illumination geometry on the spectral reflectance of multiple sensors. Our methodology involves inverting radiative transfer model variables using numerical optimization to estimate N% and creating a hybrid model. We used Gaussian process regression (GPR) to incorporate the inverted variables into the hybrid model for N% prediction, resulting in a unified approach for N% estimation across different sensors. Our model shows a validation accuracy of 0.35 (RMSE %N), a mean prediction interval width (MPIW) of 0.35, and an R (Formula presented.) of 0.50, using independent data from multiple sensors collected between 2016 and 2019. Our unified method provides a promising solution for estimating N% in vegetation from L7, L8, and S2 satellite data, overcoming the limitations posed by diverse sensor configurations and complex atmospheric interactions.
Crystal entrainment from cool, low-silica rocks into hot, high-silica melts: diverse primary melt compositions at Taranaki volcano, New Zealand
(The Geological Society of London, 2023-05-19) D'Mello N; Zellmer G; Kereszturi G; Ubide T; Procter J; Stewart R
The prevalence of antecrysts in arc volcanic rocks is widely accepted, yet the origin of their carrier melts remains debated. Crystal cargo in lava flows from Taranaki volcano, New Zealand, is dominated by plagioclase, clinopyroxene and amphibole. Except for some crystal rims, mineral phases are in disequilibrium with the melt they are entrained in. Major element chemistry reveals an almost complete compositional overlap between the crystals in the lava and those in xenoliths. The large volume fraction of crystals (35–55 vol%) exerts a strong control on whole-rock compositions, reducing silica by 5–11 wt% compared with the carrier melt. Yet there is no clear relationship between mineral proportion and bulk-rock compositions. Our data are inconsistent with extensive fractional crystallization, commonly invoked as a driver of magma evolution towards silica-rich compositions. Instead, high-temperature, aphyric carrier melts with varied compositions (55–68 wt% SiO2) entrain crystal cargo while ascending through colder, low-silica rocks. Thus, some parental melts at Taranaki volcano are significantly more silica-rich than arc basalts commonly invoked as primary magmas. Further, thermometric and hygrometric constraints preclude a deep crustal hot zone for the source of these melts, which we argue are of subcrustal origin.
Determining physical and mechanical volcanic rock properties via reflectance spectroscopy
(Elsevier B V, 2021-12) Schaefer LN; Kereszturi G; Villeneuve M; Kennedy B
There are currently no reliable methods to determine rock physical and mechanical properties that are not labor or resource intensive, especially at the scale of volcanoes. Using mineralogical-physical-mechanical relationships, we suggest it is possible to derive rock properties from rapid, non-invasive reflectance spectroscopy measurements. To demonstrate this potential, we correlate the physical and mechanical properties of variously altered andesitic volcanic rocks to laboratory reflectance spectroscopy using statistical analysis. Several rock properties, including density, connected porosity, strength, magnetic susceptibility, and elasticity, correlate with reflectance spectroscopy in both the visible and short-wave infrared parts of the electromagnetic spectrum. We attribute these correlations to the presence and degradation (i.e. weathering or hydrothermal alteration) of iron-bearing minerals such as pyroxene, magnetite, and pyrite, which reflect changes to both rock properties and reflectance spectroscopy measurements. Results support the use of transfer functions to estimate rock properties directly from reflectance spectroscopy. Ultimately, aerial or satellite imaging spectroscopy could be used to create geotechnical maps at volcano scale
Disentangling the effects of temperature and reactive minerals on soil carbon stocks across a thermal gradient in a temperate native forest ecosystem
(Springer Nature, 2024-03) Siregar IH; Camps-Arbestain M; Kereszturi G; Palmer A; Kirschbaum MUF; Wang T; Weintraub-Lef SR
Effects of global warming on soil organic carbon (C) can be investigated by comparing sites experiencing different temperatures. However, observations can be affected by covariance of temperature with other environmental properties. Here, we studied a thermal gradient in forest soils derived from volcanic materials on Mount Taranaki (New Zealand) to disentangle the effects of temperature and reactive minerals on soil organic C quantity and composition. We collected soils at four depths and four elevations with mean annual temperatures ranging from 7.3 to 10.5 °C. Soil C stocks were not significantly different across sites (average 162 MgC ha−1 to 85 cm depth, P >.05). Neither aluminium (Al)-complexed C, nor mineral-associated C changed significantly (P >.05) with temperature. The molecular characterisation of soil organic matter showed that plant-derived C declined with increasing temperature, while microbial-processed C increased. Accompanying these changes, soil short-range order (SRO) constituents (including allophane) generally increased with temperature. Results from structural equation modelling revealed that, although a warmer temperature tended to accelerate soil organic C decomposition as inferred from molecular fingerprints, it also exerted a positive effect on soil total C presumably by enhancing plant C input. Despite a close linkage between mineral-associated C and soil organic C, the increased abundance of reactive minerals at 30–85 cm depth with temperature did not increase soil organic C concentration at that depth. We therefore propose that fresh C inputs, rather than reactive minerals, mediate soil C responses to temperature across the thermal gradient of volcanic soils under humid-temperate climatic conditions
Exploring intrusive processes through the crystal cargo of volcanic rocks: The case of lava flows from Taranaki volcano, New Zealand
(Elsevier B V, 2024-11) D'Mello NG; Zellmer GF; Ubide T; Caulfield J; Usuki M; Iizuka Y; Kereszturi G; Procter JN; Stewart RB; Romano C
The present-day edifice of Taranaki volcano, New Zealand, is largely made up of lava flows extruded over approximately the last 8 kyr. The crystal cargo of plagioclase, pyroxene and amphibole in these lavas displays varied major, minor, and trace element zoning patterns, pointing to long and complex crystal growth histories. Crystal zoning patterns do not vary systematically between stratigraphic units, and multiple patterns are seen within the same sample over very short length scales. Intracrystalline elemental variations reveal mineral-melt interactions, which result in repeated resorption and recrystallisation in varied environments. Variable degrees of undercooling are evidenced by clinopyroxenes, with most crystals displaying sector zoning (ΔT < 50 K), while others only show concentric zoning, which suggests very low ΔT. The common occurrence of resorbed cores within the crystals and the prevalence of glomerocrysts indicate antecrystic and/or xenocrystic origins and crystal aggregation processes. We hypothesise that the repeated intrusion of melts into the crustal basement of Taranaki volcano has resulted in the formation of a heterogeneous subsolidus plutonic to supersolidus mushy (∼15–55 vol% crystals) system that interacts with intruding melts from the mantle. These interactions result in disaggregation of crystal clots from the plutonic intrusives and remobilization of the crystals through various sub-environments of small ephemeral mush pockets. Eruption-triggering injections of melt then pick up these crystals with varied growth histories to be extruded
Mapping a Cloud-Free Rice Growth Stages Using the Integration of PROBA-V and Sentinel-1 and Its Temporal Correlation with Sub-District Statistics
(MDPI (Basel, Switzerland), 2021-04-13) Ramadhani F; Pullanagari R; Kereszturi G; Procter J; Farooque AA
Monitoring rice production is essential for securing food security against climate change threats, such as drought and flood events becoming more intense and frequent. The current practice to survey an area of rice production manually and in near real-time is expensive and involves a high workload for local statisticians. Remote sensing technology with satellite-based sensors has grown in popularity in recent decades as an alternative approach, reducing the cost and time required for spatial analysis over a wide area. However, cloud-free pixels of optical imagery are required to pro-duce accurate outputs for agriculture applications. Thus, in this study, we propose an integration of optical (PROBA-V) and radar (Sentinel-1) imagery for temporal mapping of rice growth stages, including bare land, vegetative, reproductive, and ripening stages. We have built classification models for both sensors and combined them into 12-day periodical rice growth-stage maps from January 2017 to September 2018 at the sub-district level over Java Island, the top rice production area in Indonesia. The accuracy measurement was based on the test dataset and the predicted cross-correlated with monthly local statistics. The overall accuracy of the rice growth-stage model of PROBA-V was 83.87%, and the Sentinel-1 model was 71.74% with the Support Vector Machine classifier. The temporal maps were comparable with local statistics, with an average correlation between the vegetative area (remote sensing) and harvested area (local statistics) is 0.50, and lag time 89.5 days (n = 91). This result was similar to local statistics data, which correlate planting and the harvested area at 0.61, and the lag time as 90.4 days, respectively. Moreover, the cross-correlation between the predicted rice growth stage was also consistent with rice development in the area (r > 0.52, p < 0.01). This novel method is straightforward, easy to replicate and apply to other areas, and can be scaled up to the national and regional level to be used by stakeholders to support improved agricultural policies for sustainable rice production.
Mapping nutrient concentration in pasture using hyperspectral imaging
(2015) Yule IJ; Pullanagari RR; Irwin M; McVeagh P; Kereszturi G; White M; Manning M
Quantifying location error to define uncertainty in volcanic mass flow hazard simulations
(Copernicus Publications on behalf of the European Geosciences Union, 2021-08-20) Mead SR; Procter J; Kereszturi G
The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed ("actual") map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano, as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This "fuzzification"of simulated results yields improvements in targeted performance metrics relative to a length scale parameter at the expense of decreases in opposing metrics (e.g. fewer false negatives result in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision-making from simulated data.
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.
Volcanism and rapid sedimentation affect the benthic communities of Deception Island, Antarctica
(Elsevier B.V., 2021-05-01) Angulo-Preckler C; Pernet P; García-Hernández C; Kereszturi G; Álvarez-Valero AM; Hopfenblatt J; Gómez-Ballesteros M; Otero XL; Caza J; Ruiz-Fernández J; Geyer A; Avila C
Deception Island is amongst the most active volcanoes in the Southern Ocean, with over 20 explosive eruptions in the last ca. 200 years. The eruption that formed the caldera at Deception Island occurred 3980 ± 125 calendar years Before Present, and it is the largest eruptive event documented in Antarctica during Holocene. Since then, post-caldera volcanic activity has comprised many scattered eruptive vents across the island. Mortality of benthic organisms has been reported during the most recent eruptions occurred on the island, in 1967, 1969, and 1970 Common Era (CE), with very low abundances of organisms during the 1967–1973 CE period. Within the sea-flooded part of the caldera depression, named Port Foster, a submarine volcanic axis with several volcanic cones is observed. An interdisciplinary team sampled the best morphologically preserved volcanic edifice within Port Foster, the so-called Stanley Patch. Geophysical data traced the volcano and characterized its morphology and inner structure. Underwater scuba sampling allowed to acquire sediment and rock samples, photographs and video images of the benthic organisms and seascape. Morphology of Stanley Patch cone and textural characteristics of the collected pyroclastic rocks indicate that the volcanic edifice was originated during an explosive eruption. Furthermore, the lack of palagonitization, quenched pyroclast margins, and hyaloclastite deposits indicate that this cone has formed on-land, before the caldera floor became inundated by the seawater, highlighting the complex intra-caldera evolution of Deception Island. A sediment core from the crater was collected for sedimentological, and geochemical analysis. Antarctic climate and seasonal sea ice, together with organic degradation due to high sedimentation rates, explain the low total organic carbon data measured. The volcanic history of the island has probably avoided the development of a stable benthic community over time, similar to other Antarctic shallow communities. Moreover, the current geomorphological conditions still shape different benthic communities than in the surrounding coastal ecosystems. Stanley Patch, and the whole Port Foster, provide a natural laboratory for benchmarking the reestablishment of benthic communities on a volcanic-influenced shallow marine environment, offering relevant data for future studies evaluating global climate change effects on the Antarctic seabed.

Browsing by Author "Kereszturi G"

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