Building a model of debris avalanche hazard using geophysical remote sensing data

Author(s):  
Stuart Mead ◽  
Gabor Kereszturi ◽  
Craig Miller ◽  
Lauren Schaefer

<p>Hydrothermal alteration can progressively weaken volcanic flanks, leading to collapses and mass flows with potential hazards affecting communities and infrastructure many kilometres from the collapse source. Through a combination of geomagnetic and hyperspectral remote sensing, with field and laboratory measurements, we have developed an approach to assess and forecast these catastrophic hazards. Inversion of aerial geo-magnetic data is used to identify the subsurface structure and volume of weak (nominally altered) and strong (nominally unaltered) portions of the volcanic edifice of Mt. Ruapehu, New Zealand. Airborne hyperspectral imagery is used to classify the surface expression of hydrothermal alteration, which is combined with laboratory geotechnical measurements of field samples to estimate the strength of identified features. This data is essential to reducing the uncertainty in identifying flank collapse source areas through three-dimensional limit equilibrium modelling.</p><p>However, the range of potential collapse volumes, locations and triggering mechanisms still presents significant difficulties in forecasting the potential impacts of slope failures. Numerical mass flow models can be used to simulate debris avalanches, but it is infeasible to simulate all potential collapse scenarios to estimate the hazard. To ease the computational burden, we have developed a methodology that uses a reduced subset of potential slope failures through dimensional reduction and space-filling sampling techniques. Using debris avalanche simulations of this subset, a comprehensive mapping of debris flow impacts across the entire input space can be developed using statistical techniques. This mapping provides an efficient mechanism for understanding flank collapse hazards across a large spectrum of potential scenarios. This presentation will outline our framework for assessing and forecasting debris avalanche hazards through the integration of remote sensing surveys with geotechnical measurements.</p>

2021 ◽  
Vol 14 (16) ◽  
Author(s):  
Mehdi Maleki ◽  
Shojaeddin Niroomand ◽  
Ehsan Farahbakhsh ◽  
Soroush Modabberi ◽  
Hossein Ali Tajeddin

2013 ◽  
Vol 28 (4) ◽  
pp. 516-525 ◽  
Author(s):  
Marcelo Pedroso Curtarelli ◽  
Enner Alcântara ◽  
Camilo Daleles Rennó ◽  
Arcilan Trevenzoli Assireu ◽  
Marie Paule Bonnet ◽  
...  

2021 ◽  
Vol 6 (2) ◽  
pp. 86
Author(s):  
Bayu Raharja ◽  
Agung Setianto ◽  
Anastasia Dewi Titisari

Using remote sensing data for hydrothermal alteration mapping beside saving time and reducing  cost leads to increased accuracy. In this study, the result of multispectral remote sensing tehcniques has been compare for manifesting hydrothermal alteration in Kokap, Kulon Progo. Three multispectral images, including ASTER, Landsat 8, and Sentinel-2, were compared in order to find the highest overall accuracy using principle component analysis (PCA) and directed component analysis (DPC). Several subsets band combinations were used as PCA and DPC input to targeting the key mineral of alteration. Multispectral classification with the maximum likelihood algorithm was performed to map the alteration types based on training and testing data and followed by accuracy evaluation. Two alteration zones were succeeded to be mapped: argillic zone and propylitic zone. Results of these image classification techniques were compared with known alteration zones from previous study. DPC combination of band ratio images of 5:2 and 6:7 of Landsat 8 imagery yielded a classification accuracy of 56.4%, which was 5.05% and 10.13% higher than those of the ASTER and Sentinel-2 imagery. The used of DEM together with multispectral images was increase the accuracy of hydrothermal alteration mapping in the study area.


2006 ◽  
Vol 12 (4) ◽  
pp. 315-328 ◽  
Author(s):  
Lars T. Waser ◽  
Meinrad Kuechler ◽  
Markus Schwarz ◽  
Eva Ivits ◽  
Silvia Stofer ◽  
...  

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