Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/9034
Authors: Bartolini, S.* 
Cappello, A.* 
Martì, J.* 
Del Negro, C.* 
Title: QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility
Journal: Natural Hazards and Earth System Sciences (NHESS) 
Series/Report no.: /13(2013)
Issue Date: 27-Nov-2013
DOI: 10.5194/nhess-13-3031-2013
URL: http://www.nat-hazards-earth-syst-sci.net/13/3031/2013/nhess-13-3031-2013.html
Keywords: volcanic susceptibility
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.08. Volcanic risk 
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).
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