Clustering of infrasonic events as tool to detect and locate
explosive activity at Mt. Etna volcano
Active volcanoes characterized by open conduit conditions effectively generate sonic and infrasonic signals, whose investigation provides useful information for both monitoring purposes and study of the dynamics of explosive phenomena. At Mt. Etna volcano (Italy) a clustering algorithm based on spectral features and amplitude of the infrasonic events was developed. It allows to recognize the active vent with no location algorithm and by using only one station. Moreover, a waveform inversion procedure was coded, based on genetic algorithm, that enables us to quantitatively investigate the infrasound source parameters.