Continuous HMM-Based Seismic-Event Classification at Deception Island, Antarctica

Abstract

This paper shows a complete seismic-event classification and monitoring system that has been developed based on the seismicity observed during three summer Antarctic surveys at the Deception Island Volcano, Antarctica. The system is based on the state of the art in hidden Markov modeling (HMM) techniques successfully applied to other scenarios. A database that contains a representative set of different seismic events including volcano-tectonic earthquakes, long period (LP) events, volcanic tremor, and hybrid events that were recorded during the 1994-1995 and 1995-1996 seismic surveys was collected for training and testing. Simple left-to-right HMMs and multivariate Gaussian probability density functions with a diagonal covariance matrix were used. The feature vector consists of the log-energies of a filter bank that consists of 16 triangular weighting functions that were uniformly spaced between 0 and 20 Hz and the first- and second-order derivatives. The system is suitable to operate in real time, and its accuracy for this task is about 90%. On the other hand, when the system was tested with a different data set including mainly LP events that were registered during several seismic swarms during the 2001-2002 field survey, more than 95% of the recognized events were marked by the recognition system