Applying Ultra Low Frequency Remote Sensing Techniques in the Earthquake Precursor Analysis —Using Taiwan as an Example

Throughout worldwide, earthquakes have deprived lots of life and property. However, earthquakes cannot be predicted precisely in terms of the epicenter, time, seismic scale, and depth with various means. Most of errors were caused by misleading signal processing. The goal of this study provide a better signal processing method to depict the potential zone of seismic epicenter. In order to realize the significant signal and frequency, this study utilizes Fast Fourier Transform (FFT) to analyze Ultra Low Frequency (ULF) signals and define a warning line for dividing normal and abnormal signals. In this study, an epicenter location can be inferred by intersection of at least three abnormal angles from different stations. In addition, epicenter estimation analysis imports probability buffer concept in spatial cross analysis, moreover, this concept also applies in depth estimation. Break time estimation concludes both lots of papers information and abnormal signal pattern, so this study define that break time of earthquake is one week after abnormal signal appearance. For magnitude regression, this study utilizes three different parameter, MAEQ, MMEQ and IAEQ, to regress the correlation with Richter magnitude scale. Up to day, this study has successfully found significant signal of earthquake precursors and also calculated the potential zone of seismic epicenter, break time, depth potential and magnitude beforehand. In conclusion, this research provides a new method for epicenter prediction by analyzing ULF electromagnetic signals.