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

  • Pan Xiong
  • Xingfa Gu
  • Xuhui Shen
  • Xuemin Zhang
  • Chunli Kang
  • Yaxin Bi
Part of the Lecture Notes in Computer Science book series (LNCS, 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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pan Xiong
    • 1
    • 2
    • 3
    • 4
  • Xingfa Gu
    • 1
    • 2
    • 3
  • Xuhui Shen
    • 4
  • Xuemin Zhang
    • 4
  • Chunli Kang
    • 6
  • Yaxin Bi
    • 5
  1. 1.State Key Laboratory of Remote Sensing ScienceInstitute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal UniversityChina
  2. 2.Graduate University of Chinese Academy of SciencesChina
  3. 3.Center for National Spaceborne DemonstrationChina
  4. 4.Institute of Earthquake ScienceChina Earthquake AdministrationChina
  5. 5.School of Computing and MathematicsUniversity of UlsterUnited Kingdom
  6. 6.China Earthquake Networks CenterChina Earthquake AdministrationChina

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