Multi-Scale Trend Visualization of Long-Term Temperature Data Sets

Andreas Kerren
Linnaeus University, Department of Computer Science, ISOVIS Group, Växjö, Sweden

Ilir Jusufi
University of California, Department of Computer Science, Davis, CA, USA

Jiayi Liu
Linnaeus University, Department of Computer Science, ISOVIS Group, Växjö, Sweden

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Ingår i: Proceedings of SIGRAD 2014, Visual Computing, June 12-13, 2014, Göteborg, Sweden

Linköping Electronic Conference Proceedings 106:13, s. 91-94

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Publicerad: 2014-10-30

ISBN: 978-91-7519-212-3

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


The analysis and presentation of climate observations is a traditional application of various visualization approaches.The available data sets are usually huge and were typically collected over a long period of time. In this paper, we focus on the visualization of a specific aspect of climate data: our visualization tool was primarily developed for providing an overview of temperature measurements for one location over decades or even centuries. In order to support an efficient overview and visual representation of the data, it is based on a region-oriented metaphor that includes various granularity levels and aggregation features.


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