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Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data
November/December 2010 (vol. 16 no. 6)
pp. 1413-1420
ASCII Text
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Xiaoru Yuan, He Xiao, Hanqi Guo, Peihong Guo, Wesley Kendall, Jian Huang, Yongxian Zhang, "Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1413-1420, November/December, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2010.192,
author = {Xiaoru Yuan and He Xiao and Hanqi Guo and Peihong Guo and Wesley Kendall and Jian Huang and Yongxian Zhang},
title = {Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {16},
number = {6},
issn = {1077-2626},
year = {2010},
pages = {1413-1420},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.192},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data
IS - 6
SN - 1077-2626
SP1413
EP1420
EPD - 1413-1420
A1 - Xiaoru Yuan,
A1 - He Xiao,
A1 - Hanqi Guo,
A1 - Peihong Guo,
A1 - Wesley Kendall,
A1 - Jian Huang,
A1 - Yongxian Zhang,
PY - 2010
KW - Earth Science Visualization
KW - Multivariate Visualization
KW - Seismic Data
KW - Scalable Visualization
VL - 16
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Xiaoru Yuan, Peking University
He Xiao, Peking University
Hanqi Guo, Peking University
Peihong Guo, Peking University
Wesley Kendall, University of Tennessee
Jian Huang, University of Tennessee
Yongxian Zhang, China Earthquake Networks Center
Over the past few years, large human populations around the world have been affected by an increase in significant seismic activities. For both conducting basic scientific research and for setting critical government policies, it is crucial to be able to explore and understand seismic and geographical information obtained through all scientific instruments. In this work, we present a visual analytics system that enables explorative visualization of seismic data together with satellite-based observational data, and introduce a suite of visual analytical tools. Seismic and satellite data are integrated temporally and spatially. Users can select temporal ;and spatial ranges to zoom in on specific seismic events, as well as to inspect changes both during and after the events. Tools for designing high dimensional transfer functions have been developed to enable efficient and intuitive comprehension of the multi-modal data. Spread-sheet style comparisons are used for data drill-down as well as presentation. Comparisons between distinct seismic events are also provided for characterizing event-wise differences. Our system has been designed for scalability in terms of data size, complexity (i.e. number of modalities), and varying form factors of display environments.

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Index Terms:
Earth Science Visualization, Multivariate Visualization, Seismic Data, Scalable Visualization
Citation:
Xiaoru Yuan, He Xiao, Hanqi Guo, Peihong Guo, Wesley Kendall, Jian Huang, Yongxian Zhang, "Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1413-1420, Nov.-Dec. 2010, doi:10.1109/TVCG.2010.192
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