Discrimination of Seismic Signals in UGM Antenna Station Recordings at Merapi Volcano Using a Remote Seismic Array: Beamforming and FK Analysis

This study presents a monitoring system of Merapi Volcano activity using five remote seismic station and low-cost Raspberry Shake and Boom sensors as an alternative to conventional (local) monitoring. The purpose of this study is to identify volcanic events recorded from seismic stations (UGM antenna) on seismic signal components by detecting and classifying events. The identification of volcanic events is carried out using STA/LTA detection, spectral, temporal, and seismic array analysis, as well as classification using the beamforming approach method and Frequency-Wavenumber (FK) analysis to determine the direction of incidence of the signal. The data analyzed for the period August 16 to September 12, 2023 on seismic signal components from UGM antenna station recordings. The results of our research show that both approaches used for the event identification process are able to verify and distinguish the source of seismic signal events recorded at the seismic remote UGM antenna station. The results of the beamforming approach and FK analysis effectively distinguish volcanic and earthquake event signals, with 376 volcanic events identified and a match rate of 84.30% to the PVMBG catalogue. The UGM antenna station recording data proved to be able to record volcanic activity from a distance of ± 16 km and has the potential to be a monitoring and early warning solution in volcanic areas that do not have adequate equipment.