Repositorio
Institucional

Huenupan, Fernando

Soto, Ricardo#Meza, Pablo#Curilem, Millaray#Franco, Luis

Spectro-temporal features applied to the automatic classification of volcanic seismic events

ELSEVIER

JOURNAL OF VOLCANOLOGY AND GEOTHERMAL RESEARCH

en

Feature extraction and selection are very relevant processes in the design of automatic classifiers. In the context of volcanic seismic signal classification, most of the features presented in the literature have been extracted separately from a single domain, such as time or frequency. However, spectrograms, which combine time and frequency information, are widely used by experts during the classification of manual seismic events. This paper proposes to evaluate the performance of classifiers trained with features extracted from the spectro-temporal domain, individually or combined with other conventional features. The parameters were extracted from the spectrogram, based on a curve which combines the high energy components and the frequency bandwidth information through the duration of the event. The tests were performed at the Llaima volcano and seismic events were classified into four classes: long-period, tremor, volcano-tectonic and tectonic, using a database of signals recorded between the years 2009 and 2017. The main achievements of this study were the reduction of more than 70% of the error and false positive rates and also a reduction of approximately 30% of the number of features, compared with a baseline established in previous studies. Thus, the inclusion of spectra-temporal information was considered relevant to complement the conventional features and to support classification. (C) 2018 Elsevier B.V. All rights reserved.

Artículo original

The authors would like to thank the project FONDEF IDeA IT15I10027 for financing this study. Also, the authors would like to thank OVDAS, which provided the data and geological knowledge that supported the analysis of the results.

Los autores agradecen al proyecto FONDEF IDeA IT15I10027 por la financiación de este estudio. Asimismo, agradecen a OVDAS, que proporcionó los datos y el conocimiento geológico que respaldaron el análisis de los resultados.

10.1016/j.jvolgeores.2018.04.025

pdf

Volcano monitoring# Signal processing# Pattern recognition# Spectrogram# Spectro-temporal curves

http://dx.doi.org/10.1016/j.jvolgeores.2018.04.025

Geosciences, Multidisciplinary

Monitoreo de volcanes# Procesamiento de señales# Reconocimiento de patrones# Espectrograma# Curvas espectro-temporales

Vulcanología

Ciencias de la Computación

Geociencias

WOS:000439678100015

Spectro-temporal features applied to the automatic classification of volcanic seismic events

Artículo original

version publicada

ELSEVIER

JOURNAL OF VOLCANOLOGY AND GEOTHERMAL RESEARCH

Geociencias, Multidisciplinar

0377-0273

en

ANID FONDEF IDeA IT15I10027

The authors would like to thank the project FONDEF IDeA IT15I10027 for financing this study. Also, the authors would like to thank OVDAS, which provided the data and geological knowledge that supported the analysis of the results.

pdf

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