Clustering and visualization of earthquake data in a grid environment

Dave A. Yuen, Benjamin J. Kadlec, Evan F. Bollig, Witold Dzwinel, Zachary A. Garbow, Cesar R.S. da Silva

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

We present a web client-server service WEB-IS, which we have developed for remote analysis and visualization of seismic data consisting of both small magnitude events and large earthquakes. We show that the problem-solving environment (PSE) intended for prediction of large magnitude earthquakes can be based on this WEB-IS idea. The clustering schemes, feature generation, feature extraction techniques and rendering algorithms form a computational framework of this environment. On the other hand, easy and fast access both to the seismic data distributed among distant computing resources and to computational and visualization resources can be realized in a GRID framework. We discuss the usefulness of NaradaBrokering (iNtegrated Asynchronous Real-time Adaptive Distributed Architecture) as a middleware, allowing for flexibility and high throughput for remote visualization of geophysical data. The WEB-IS functionality was tested both on synthetic and the actual earthquake catalogs. We consider the application of similar methodology for tsunami alerts.

Original languageEnglish (US)
Pages (from-to)1-12
Number of pages12
JournalVisual Geosciences
Volume10
Issue number1
DOIs
StatePublished - Jan 2005

Bibliographical note

Funding Information:
Acknowledgements We would like to thank Yunsong Wang for contributing ideas and figures, Zhenyu Lu for his help with Na-radaBrokering, and Dr. Gordon Erlebacher for always presenting us with new ideas. We thank Professors Seth Stein and Emile Okal for discussions concerning the excitation of the normal modes in the Sumatran earthquake. WD acknowledges support from the Polish Committee for Scientific Research (KBN) Grant No. 3T11C05926. This research has been supported by Math-Geo and ITR programs of the National Science Foundation and the Digital Technology Center of the Univ. of Minnesota.

Keywords

  • Clustering
  • Earthquakes
  • Grid computing
  • PSE
  • Seismic data
  • Visualization

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