DocumentCode
1364999
Title
Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data
Author
Yuan, Xiaoru ; He Xiao ; Guo, Hanqi ; Guo, Peihong ; Kendall, Wesley ; Huang, Jian ; Zhang, Yongxian
Author_Institution
Key Lab. of Machine Perception, Peking Univ., Beijing, China
Volume
16
Issue
6
fYear
2010
Firstpage
1413
Lastpage
1420
Abstract
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.
Keywords
data visualisation; geographic information systems; research and development; seismology; geographical information; satellite based observational data; scalable multivariate analytics; scientific research; seismic based observational data; visual analytics system; Catalogs; Data visualization; Earthquakes; Image color analysis; Satellites; Three dimensional displays; Transfer functions; Earth Science Visualization; Multivariate Visualization; Scalable Visualization; Seismic Data;
fLanguage
English
Journal_Title
Visualization and Computer Graphics, IEEE Transactions on
Publisher
ieee
ISSN
1077-2626
Type
jour
DOI
10.1109/TVCG.2010.192
Filename
5613482
Link To Document