QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

Abstract

Abstract. One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps (i.e., the spatial probability of a future vent opening given the past eruptive activity of a volcano). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source geographic information system Quantum GIS, which is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows the selection of an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

Volcanic Unrest Simulation Exercises: Checklists and Guidance Notes

“…The VUELCO exercises have proved that VUSE can be used successfully to test in simulated real time the merits of probabilistic methods and tools such as BET_EF (Bayesian Event Tree for Eruption Forecasting), HASSET (Hazard Assessment Event Tree) and QVAST (Quantifying Volcanic Susceptibility) (Sandri et al 2009;Sobradelo and Bartolini 2014;Bartolini et al 2013).…”

Susceptibility of intrusion-related landslides at volcanic islands: the Stromboli case study

“…), which help to identify previous behaviour of the volcanic area, and on the changes occurring in regional and/or local stress fields originating from tectonic or lithological contrasts. One available tool to determine the volcanic susceptibility is QVAST tool (Bartolini et al 2013), which determines the probability density function (PDF) based on kernel density estimation. This probabilistic method depends on the combination of different factors such as the size of the volcanic field, the degree of clustering and the density of the volcano-structural data (Cappello et al 2012;Bartolini etal.2013;Becerrilet al2013).…”

“…The PDFs were obtained for each type of structural data with the method of the least square cross validation method (LSCV; Bartolini et al 2013;Becerril et al 2013) to obtain the bandwidth parameter, as it was the best method to represent the distribution of analysed data, and Fig. 3 a Workflow adopted in this study.…”

“…The effects of other triggers (rainfall, sea waves, seismic shaking) were not considered here. The landslides predisposing factors were estimated by random forest (RF) technique (Catani et al 2013;Ciampalini et al 2015), while the probabilistic volcanic vent opening distribution, as proxy for magma injection, was evaluated by QVAST tool (Bartolini et al 2013). The reasons to apply this methodology to Stromboli volcano are based on the following facts: (i) it has experienced moderate to huge landslides (Tibaldi 2001), (ii) it is geomorphologically prone to instability events (Nolesini et al 2013), (iii) it is affected by active intense volcanic activity that can significantly affect the stability of slopes (Di Traglia et al 2014a) and (iv) its flank instability could affect areas inhabited and intensely frequented by people for touristic activities (Nave et al 2010).…”

Stress Controls of Monogenetic Volcanism: A Review

“…While in central volcanoes it is generally assumed that future eruptions will occur through the same vents that have been active in the past, in monogenetic systems forecasting the position of new vents is much more challenging due to this lack of a permanent shallow stress configuration. Spatial analysis addressed to infer the location of future vents (volcanic susceptibility, see Martí and Felpeto, 2010) in monogenetic volcanism generally assumes that the next eruption will occur close to the location of the previous ones (Connor, 1990;Connor et al, 1992Ho, 1992Ho, , 1995Martin et al, 1994;Ho and Smith, 1998;Alberico et al, 2002;Martí and Felpeto, 2010;Bebbington and Cronin, 2011;Cappello et al, 2012;Selva et al, 2012;Bartolini et al, 2013;Becerril et al, 2013a;Le Corvec et al, 2013a;Bevilacqua et al, 2015). The reason to make this assumption is based on the fact that in last eruptive episodes volcanoes had formed near previous ones (forming a cluster), so we assume that this behavior will continue.…”