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A Wavelet-Based Method for Detecting Seismic Anomalies in Remote Sensing Satellite Data

Xiong, Pan, Bi, Yaxin and Shen, Xuhui (2009) A Wavelet-Based Method for Detecting Seismic Anomalies in Remote Sensing Satellite Data. In: Machine Learning and Data Mining in Pattern Recognition Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp. 569-581. ISBN 978-3-642-03069-7 [Book section]

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Abstract

In this paper we present a comparative analysis of two types of remote sensing satellite data by using the wavelet-based data mining techniques. The analyzed results reveal that the anomalous variations exist related to 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 anomalies in remote sensing 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:25493
Deposited By: Dr Yaxin Bi
Deposited On:21 Jan 2016 16:28
Last Modified:21 Jan 2016 16:28

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