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

نویسندگان

  • Andreas Kerren
  • Ilir Jusufi
  • Jiayi Liu
چکیده

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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تاریخ انتشار 2014