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Issue No.06 - November/December (2010 vol.16)
pp: 1413-1420
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
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 & Computer Graphics, vol.16, no. 6, pp. 1413-1420, November/December 2010, doi:10.1109/TVCG.2010.192
[1] V. Akcelik, J. Bielak, G. Biros, I. Epanomeritakis, A. Fernandez, O. Ghattas, E. J. Kim, J. Lopez, D. O'Hallaron, T. Tu, and J. Urbanic, High resolution forward and inverse earthquake modeling on terascale computers. In SC'03: Proc. of ACM/IEEE Supercomputing, page 52, 2003.
[2] M. Antolik, C. Stidham, D. Dreger, S. Larsen, A. Lomax, and B. Romanowicz, 2-D and 3-D models of broadband wave propagation in the San Francisco Bay region and North Coast ranges. Seismological Research Letters, 68 (328), 1997.
[3] U. Brandes and C. Pich, Eigensolver methods for progressive multidimensional scaling of large data. In Graph Drawing, pages 42–53, 2006.
[4] P. Chopra, J. Meyer, and A. Fernandez, Immersive volume visualization of seismic simulations: a case study of techniques invented and lessons learned. In Proc. of IEEE Visualization, pages 497–500, 2002.
[5] A. Chourasia and S. Cutchin, and B. Aagaard, Visualizing the ground motions of the 1906 San Francisco Earthquake. Computers and Geosciences, 34 (12): 1798–1805, 2008.
[6] A. Chourasia, S. Cutchin, Y. Cui, R. W. Moore, K. Olsen, S. M. Day, J. B. Minster, P. Maechling, and T. H. Jordan, Visual insights into high-resolution earthquake simulations. IEEE Comput. Graph. Appl. 27 (5): 28–34, 2007.
[7] CSMonitor. 2010/0405Why-Mexicali-earthquake-damage-is-nothing-compared-to-Haiti, 2010.
[8] S. Daily, Science news, first satellite map of haiti earthquake. 01100114143323.htm.
[9] W. Dzwinel, D. A. Yuen, K. Boryczko, Y. Ben-Zion, S. Yoshioka, and T. Ito, Nonlinear multidimensional scaling and visualization of earthquake clusters over space, time and feature space. Nonlinear Processes in Geophysics, 12: 117–128, 2005.
[10] M. Glatter, J. Huang, S. Ahern, J. Daniel, and A. Lu, Visualizing temporal patterns in large multivariate data using textual pattern matching. IEEE Trans. on Visualization & Computer Graphics, 14 (6): 1467–1474, 2008.
[11] K. Hirahara, N. Kato, T. Miyatake, T. Hori, M. Hyodo, J. Inn, N. Mitsui, Y. Wada, T. Miyamura, Y. Nakama, T. Kanai, and M. Iizuka, Simulation of earthquake generation process in a complex system of faults. Technical report, Earth Simulator Center, 2004.
[12] T.-J. Hsieh, Understanding earthquakes with advanced visualization. ACM SIGGRAPH Comput. Graph., 44 (1): 1–13, 2010.
[13] T.-J. Hsieh, C.-K. Chen, and K.-L. Ma, Visualizing field-measured seismic data. In Proc. of IEEE Pacific Visualization Symp., pages 65–72, March 2010.
[14] G. Humphreys, M. Houston, R. Ng, R. Frank, S. Ahern, P. D. Kirch-ner, and J. T. Klosowski, Chromium: a stream-processing framework for interactive rendering on clusters. ACM Trans. Graph., 21 (3): 693–702, 2002.
[15] A. Inselberg, The plane with parallel coordinates. The Visual Computer, 1 (2): 69–91, 1985.
[16] A. Inselberg and B. Dimsdale, Parallel coordinates: a tool for visualizing multi-dimensional geometry. In Proc. of IEEE Visualization, pages 361–378, 1990.
[17] W. Kendall, M. Glatter, J. Huang, T. Peterka, R. Latham, and R. Ross, Terascale data organization for discovering multivariate climatic trends. In SC'09: Proc. of ACM/IEEE Supercomputing, page 1, 2009.
[18] J. Kniss, S. Premoze, M. Ikits, A. Lefohn, C. Hansen, and E. Praun, Gaussian transfer functions for multi-field volume visualization. In Proceedings of IEEE Visualization 2003, pages 65–73, 2003.
[19] D. Komatitsch, S. Tsuboi, C. Ji, and J. Tromp, A 14.6 billion degrees of freedom, 5 teraflops, 2.5 terabyte earthquake simulation on the earth simulator. In SC'03: Proc. of ACM/IEEE Supercomputing, page 4, 2003.
[20] K.-L. Ma, In situ visualization at extreme scale: challenges and opportunities. IEEE Comput. Graph. Appl., 29 (6): 14–19, 2009.
[21] K.-L. Ma, A. Stompel, J. Bielak, O. Ghattas, and E. J. Kim, Visualizing very large-scale earthquake simulations. In SC'03: Proc. of ACM/IEEE Supercomputing, page 48, 2003.
[22] G. P. Mavroeidis and A. S. Papageorgiou, Simulation of long-period near-field ground motion for the great 1906 San Francisco earthquake. Seismological Research Letters, 72 (2): 227, 2001.
[23] K. Mogi, Some features of recent seismic activity in and near japan (2), activity before and after great earthquakes. Bull. Earthq. Res. Inst., pages 395–417, 1969.
[24] T. Naka, M. Yamada, M. Endo, S. Miyazaki, and J. Hasegawa, Visualization of seismic-center distribution data for earthquake prediction. In Proc. of Nicograph Intl, Session V Simulation, 2006.
[25] NASA. Global Earthquake Satellite System (GESS). http://solidearth.jpl.nasa.govgess.html, 2010.
[26] D. Patel, C. Giertsen, J. Thurmond, J. Gjelberg, and M. E. Groller, The seismic analyzer - interpreting and illustrating 2D seismic data. IEEE Trans. on Visual. & Comput. Graph., 14 (6): 1571–1578, Oct. 2008.
[27] S. Potts, M. Tory, and T. Moller, A parallel coordinates interface for exploratory volume visualization. In Proc. of IEEE Vis, page 102, 2003.
[28] J. Rundle, W. Klein, and S. Gross, Physical basis for statistical patterns in complex earthquake populations: Models, predictions and tests. Pure and Appl. Geophys., 155 (2-4): 575–607, 1999.
[29] V. Sgrignal, C. Information, R. Console, L. Conti, A. M. Galper, V. Malvezzil, M. Parrot, P. Picozza, R. Scrimaglio, P. Spillantini, and D. Zilpimiani, The esperia project: a mission to investigate the near-earth space. Earth Observation with CHAMP, pages 407–412, 2005.
[30] T. Tu, H. Yu, L. Ramirez-Guzman, J. Bielak, O. Ghattas, K.-L. Ma, and D. R. O'Hallaron, From mesh generation to scientific visualization: an end-to-end approach to parallel supercomputing. In SC'06: Proc. of ACM/IEEE Supercomputing, page 91, 2006.
[31] R. H. WolfeJr. and C. N. Liu, Interactive visualization of 3D seismic data: a volumetric method. IEEE Comput. Graph. Appl., 8 (4): 24–30, 1988.
[32] M. Wyss, P. Bodin, and R. E. Habermann, Seismic quiescence at park-field: an independent indication of an imminent earthquake. Nature, 345: 426–428, 1990.
[33] M. Wyss and R. E. Habermann, Precursory quiescence. Pure and Appl. Geophys., 126: 319–332, 1988.
[34] H. Yu, K.-L. Ma, and J. Welling, A parallel visualization pipeline for terascale earthquake simulations. In SC'04: Proc. of ACM/IEEE Super-computing, page 49, 2004.
[35] X. Yuan, P. Guo, H. Xiao, H. Zhou, and H. Qu, Scattering points in parallel coordinates. IEEE Trans. on Visual. & Comput. Graph., 15 (6): 1001–1008, 2009.
[36] D. A. Yuen, B. J. Kadlec, E. F. Bollig, W. Dzwinel, Z. A. Garbow, and C. R.S. da Silva, Clustering and visualization of earthquake data in a grid environment. Visual Geosciences, pages 1–12, 2005.
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