Please use this identifier to cite or link to this item:
Authors: Cannavò, Flavio* 
Cannata, Andrea* 
Cassisi, Carmelo* 
Di Grazia, Giuseppe* 
Montalto, Placido* 
Prestifilippo, Michele* 
Privitera, Eugenio* 
Coltelli, Mauro* 
Gambino, Salvatore* 
Title: A multivariate probabilistic graphical model for real-time volcano monitoring on Mount Etna
Issue Date: 20-Apr-2017
Series/Report no.: /122 (2017)
DOI: 10.1002/2016JB013512
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.
Appears in Collections:Papers Published / Papers in press

Files in This Item:
File Description SizeFormat 
Cannav-_et_al-2017-Journal_of_Geophysical_Research-_Solid_Earth.pdf2.81 MBAdobe PDFView/Open
Show full item record

Page view(s)

checked on Mar 20, 2018


checked on Mar 20, 2018

Google ScholarTM