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

Xiong, Pan, Gu, Xingfa, Shen, Xuhui, Zhang, Xueming, Kang, Chunli and Bi, Yaxin (2011) Wavelet-Based Method for Detecting Seismic Anomalies in DEMETER Satellite Data. In: Knowledge Science, Engineering and Management. Springer Berlin Heidelberg, pp. 1-11. ISBN 978-3-642-25974-6 [Book section]

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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.

Item Type:Book section
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:25480
Deposited By: Dr Yaxin Bi
Deposited On:19 Jan 2016 09:37
Last Modified:19 Jan 2016 09:37

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