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

Pan Xiong, Xingfa Gu, Xuhui Shen, Xueming Zhang, Chunli Kang, Yaxin Bi

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationKnowledge Science, Engineering and Management
PublisherSpringer
Pages1-11
ISBN (Print)978-3-642-25974-6
Publication statusPublished - 2011

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  • Cite this

    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 Knowledge Science, Engineering and Management (pp. 1-11). Springer.