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December 2002, Volume 1, Number 3-4, Pages 182-193
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| Original Article |
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| Multivariate visualization with data fusion |
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| Pak Chung Wong1, Harlan Foote1, David L Kao2, Ruby Leung1 and Jim Thomas1 |
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1Pacific Northwest National Laboratory, Washington, U.S.A
2NASA Ames Research Center, California, U.S.A
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Correspondence to: Pak Chung Wong, P.O. Box 999, K7-28, Richland, WA 99352, U.S.A. Tel: 509 372 4764; Fax: 509 375 2641; E-mail: pak.wong@pnl.gov |
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| Abstract |
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We discuss a fusion-based visualization method to analyze a multivariate climate dataset and its metadata. The primary difference between a conventional visualization and a fusion-based visualization is that the former draws on a single image whereas the latter draws on multiple see-through layers, which are then overlaid on each other to form the final visualization. We propose optimized colormaps to highlight subtle features that would not be shown with conventional colormaps. We present fusion techniques that integrate multiple single-purpose visualization techniques into the same viewing space. Our highly flexible fusion approach allows scientists to explore multiple parameters concurrently by mixing and matching images without frequently reconstructing new visualizations from the data for every possible combination. Although our primary visualization application is climate modeling, we show with examples that our fundamental design - fusing layers of data images for multivariate visualization - can be generalized for other information visualization applications. Information Visualization (2002) 1, 182-193. doi:10.1057/palgrave.ivs.9500024 |
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| Keywords |
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Multivariate visualization; data fusion; color mapping; flow field visualization; information visualization; climate modeling |
| Received 14 October 2002; revised 26 October 2002; accepted 26 October 2002 |
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