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  • Kereszturi, Gabor, et al. (author)
  • Porosity, strength, and alteration - Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy
  • 2023
  • In: Earth and Planetary Science Letters. - : Elsevier. - 0012-821X .- 1385-013X. ; 602
  • Journal article (peer-reviewed)abstract
    • Volcano slope stability analysis is a critical component of volcanic hazard assessments and monitoring. However, traditional methods for assessing rock strength require physical samples of rock which may be difficult to obtain or characterize in bulk. Here, visible to shortwave infrared (350-2500 nm; VNIR-SWIR) reflected light spectroscopy on laboratory-tested rock samples from Ruapehu, Ohakuri, Whakaari, and Banks Peninsula (New Zealand), Merapi (Indonesia), Chaos Crags (USA), Styrian Basin (Austria) and La Soufriere de Guadeloupe (Eastern Caribbean) volcanoes was used to design a novel rapid chemometric-based method to estimate uniaxial compressive strength (UCS) and porosity. Our Partial Least Squares Regression models return moderate accuracies for both UCS and porosity, with R2 of 0.43-0.49 and Mean Absolute Percentage Error (MAPE) of 0.2-0.4. When laboratory-measured porosity is included with spectral data, UCS prediction reaches an R2 of 0.82 and MAPE of 0.11. Our models highlight that the observed changes in the UCS are coupled with subtle mineralogical changes due to hydrothermal alteration at wavelengths of 360-438, 532-597, 1405-1455, 2179-2272, 2332-2386, and 2460-2490 nm. These mineralogical changes include mineral replacement, precipitation hydrothermal alteration processes which impact the strength of volcanic rocks, such as mineral replacement, precipitation, and/or silicification. Our approach highlights that spectroscopy can provide a first order assessment of rock strength and/or porosity or be used to complement laboratory porosity-based predictive models. VNIR-SWIR spectroscopy therefore provides an accurate non-destructive way of assessing rock strength and alteration mineralogy, even from remote sensing platforms. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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