“…For these tasks, a large number of methods have been proposed such as a statistical method using Weibull analysis and a non-homogeneous generalized Pareto-Poisson process [83], a mixture of exponentials distributions [84], a Bayesian event tree to estimate volcanic hazard (BET VH) [85][86][87], a Bayesian event tree for eruption forecasting [88], the extreme value theory [89] A detailed description of GIS and their application to natural hazards is presented by Tarolli and Cavalli [101]. Such analysis of data has allowed addressing many applications such as analysis of lava ows [95], discrimination of volcanic ashes according to textures [102], ranking of volcanic threats [103], zonation of volcanic hazards [104], zonation of lava ow [105], analysis of sensitivity to lahar hazards for variations in exposed population [106], forecast of style and size of eruptions [82], pattern recognition of volcanic tremor data [107], management of volcanic crises [108], modelling of volcanic source [90], location of incipient volcanic vents [75], characterization of thermal volcanic activities [91], land-use and contingency planning as risk mitigation strategies [80], and development of volcanic alert systems [109].…”