Abstract
Stereo-observation, being comprised of both ground-and space-based observations, is an important approach for likely making earthquake prediction to break through. The electromagnetic observation is considered as one of the most important measures in the stereo-observation, and should be one of the fields in which breakthrough is firstly and likely made and would be an effective device to obtain information for earthquake pre-warning. New techniques of alternating electromagnetic field observation, e.g., Controlled-Source Extremely Low Frequency (CSELF) and satellite observation, are gradually applied to the earthquake monitoring, which contain the more abundant information than those mainly observed in constant electric or magnetic field. This will increase the amount of recorded data greatly and inevitably require the robust techniques of data processing and analyzing. Previous analysis techniques mainly utilize the Fourier transform method for alternating electromagnetic field data, which cannot consider the information in time and frequency domains simultaneously. In this study we try to use the wavelet transform method to process alternating electromagnetic field data and carry out a case study, which aims to obtain the electromagnetic anomaly information in both frequency- and time-domains. The study is conducted on the data observed for 35 days during the strong aftershock period after the Lushan earthquake with Ms=7.0 in the Sichuan province in China. The preliminary results show that the wavelet transform method has an advantage and potential for identifying the electromagnetic anomalies relative to the earthquake events.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | European Space Agency |
Number of pages | 8 |
Publication status | Published (in print/issue) - 30 Sept 2014 |
Event | Dragon 3 symposium. ESA Communications. 8 pp - Chengdu, China Duration: 30 Sept 2014 → … |
Conference
Conference | Dragon 3 symposium. ESA Communications. 8 pp |
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Period | 30/09/14 → … |
Keywords
- Electromagnetic data
- Anomaly detection
- Earthquake