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
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;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2010.192