A multivariate probabilistic graphical model for real‐time volcano monitoring on Mount Etna
Flavio Cannavò, Andrea Cannata, Carmelo Cassisi, Giuseppe Di Grazia, P. Montalto, Michele Prestifilippo, E. Privitera, M. Coltelli, Salvatore Gambino · Journal of Geophysical Research Solid Earth · 2017
Abstract Real‐time assessment of the state of a volcano plays a key role for civil protection purposes. Unfortunately, because of the coupling of highly nonlinear and partially known complex volcanic processes, and the intrinsic uncertainties in measured parameters, the state of a volcano needs to be expressed in probabilistic terms, thus making any rapid assessment sometimes impractical. With the aim of aiding on‐duty personnel in volcano‐monitoring roles, we present an expert system approach to automatically estimate the ongoing state of a volcano from all available measurements. The system consists of a probabilistic model that encodes the conditional dependencies between measurements and volcanic states in a directed acyclic graph and renders an estimation of the probability distribution of the feasible volcanic states. We test the model with Mount Etna (Italy) as a case study by considering a long record of multivariate data. Results indicate that the proposed model is effective for early warning and has considerable potential for decision‐making purposes.