TY  - JOUR
A1  - Zali, Zahra
A1  - Ohrnberger, Matthias
A1  - Scherbaum, Frank
A1  - Cotton, Fabrice
A1  - Eibl, Eva P. S.
T1  - Volcanic tremor extraction and earthquake detection using music information retrieval algorithms
JF  - Seismological research letters
N2  - Volcanic tremor signals are usually observed before or during volcanic eruptions and must be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contrib-ute to improving upon our understanding of the underlying physical processes. Exploiting the idea of harmonic-percussive separation in musical signal processing, we develop a method to extract the harmonic volcanic tremor signals and to detect tran-sient events from seismic recordings. Based on the similarity properties of spectrogram frames in the time-frequency domain, we decompose the signal into two separate spec-trograms representing repeating (harmonic) and nonrepeating (transient) patterns, which correspond to volcanic tremor signals and earthquake signals, respectively. We reconstruct the harmonic tremor signal in the time domain from the complex spectrogram of the repeating pattern by only considering the phase components for the frequency range in which the tremor amplitude spectrum is significantly contribut-ing to the energy of the signal. The reconstructed signal is, therefore, clean tremor signal without transient events. Furthermore, we derive a characteristic function suitable for the detection of tran-sient events (e.g., earthquakes) by integrating amplitudes of the nonrepeating spectro-gram over frequency at each time frame. Considering transient events like earthquakes, 78% of the events are detected for signal-to-noise ratio = 0.1 in our semisynthetic tests. In addition, we compared the number of detected earthquakes using our method for one month of continuous data recorded during the Holuhraun 2014-2015 eruption in Iceland with the bulletin presented in Agustsdottir et al. (2019). Our single station event detection algorithm identified 84% of the bulletin events. Moreover, we detected a total of 12,619 events, which is more than twice the number of the bulletin events.
KW  - algorithms
KW  - body waves
KW  - earthquakes
KW  - elastic waves
KW  - eruptions
KW  - geologic hazards
KW  - natural hazards
KW  - P-waves
KW  - S-waves
KW  - seismic waves
KW  - signal-to-noise ratio
KW  - swarms
KW  - volcanic earthquakes
Y1  - 2021
U6  - https://doi.org/10.1785/0220210016
SN  - 0895-0695
SN  - 1938-2057
VL  - 92
IS  - 6
SP  - 3668
EP  - 3681
PB  - Seismological Society of America
CY  - Boulder, Colo.
ER  -