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. © 2011 Springer-Verlag.
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CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7091 LNAI, pp. 1–11). https://doi.org/10.1007/978-3-642-25975-3_1
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