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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Wavelet-Based Method for Detecting Seismic Anomalies in DEMETER Satellite Data
verfasst von : Pan Xiong, Xingfa Gu, Xuhui Shen, Xuemin Zhang, Chunli Kang, Yaxin Bi
Erschienen in: Knowledge Science, Engineering and Management
Verlag: Springer Berlin Heidelberg
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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.