Issue No. 06 - November/December (2010 vol. 16)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.192
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.
Earth Science Visualization, Multivariate Visualization, Seismic Data, Scalable Visualization
X. Yuan et al., "Scalable Multi-variate Analytics of Seismic and Satellite-based Observational Data," in IEEE Transactions on Visualization & Computer Graphics, vol. 16, no. , pp. 1413-1420, 2010.