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Wavelet-Based Method for Detecting Seismic Anomalies in DEMETER Satellite Data

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7091)

Abstract

In this paper we present an analysis of DEMETER (Detection of Electromagnetic Emissions Transmitted from Earthquake Regions) satellite data by using the wavelet-based data mining techniques. The analyzed results reveal that the possible anomalous variations exist around the earthquakes. The methods studied in this work include wavelet transformations and spatial/temporal continuity analysis of wavelet maxima. These methods have been used to analyze the singularities of seismic precursors in DEMETER satellite data, which are associated with the two earthquakes of Wenchuan and Pure recently occurred in China.

Keywords

  • Wenchuan Earthquake
  • Conjugate Point
  • Wavelet Method
  • Earthquake Region
  • Abnormal Event

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Xiong, P., Gu, X., Shen, X., Zhang, X., Kang, C., Bi, Y. (2011). Wavelet-Based Method for Detecting Seismic Anomalies in DEMETER Satellite Data. In: Xiong, H., Lee, W.B. (eds) Knowledge Science, Engineering and Management. KSEM 2011. Lecture Notes in Computer Science(), vol 7091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25975-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-25975-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25974-6

  • Online ISBN: 978-3-642-25975-3

  • eBook Packages: Computer ScienceComputer Science (R0)