Automatic Arrival Time Detection for Earthquakes Based on Stacked Denoising Autoencoder

Omar M. Saad, Koji Inoue, Ahmed Shalaby, Lotfy Samy, Mohammed S. Sayed

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


The accurate detection of P-wave arrival time is imperative for determining the hypocenter location of an earthquake. However, precise detection of onset time becomes more difficult when the signal-to-noise ratio (SNR) of the seismic data is low, such as during microearthquakes. In this letter, a stacked denoising autoencoder (SDAE) is proposed to smooth the background noise. The SDAE acts as a denoising filter for the seismic data. In the proposed algorithm, the SDAE is utilized to reduce background noise such that the onset time becomes more clear and sharp. Afterward, a hard decision with one threshold is used to detect the onset time of the event. The proposed algorithm is evaluated on both synthetic and field seismic data. As a result, the proposed algorithm outperforms the short-time average/long-time average and the Akaike information criterion algorithms. The proposed algorithm accurately picks the onset time of 94.1% for 407 field seismic waveforms with a standard deviation error of 0.10 s. In addition, the results indicate that the proposed algorithm can pick arrival times accurately for weak SNR seismic data with SNR higher than -14 dB.

Original languageEnglish
Article number8437146
Pages (from-to)1687-1691
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Issue number11
Publication statusPublished - Nov 2018

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering


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