ContourDiff: Revealing Differential Trends in Spatiotemporal Data

Zonayed Ahmed, Michael Beyene, Debajyoti Mondal, C. Roy, Christopher Dutchyn, Kevin A. Schneider
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引用次数: 2

Abstract

Changes in spatiotemporal data may often go unnoticed due to their inherent noise and low variability (e.g., geological processes over years). Commonly used approaches such as side-by-side contour plots and spaghetti plots do not provide a clear idea about the temporal changes in such data. We propose ContourDiff, a vector-based visualization over contour plots to visualize the trends of change across spatial regions and temporal domain. Our approach first aggregates for each location, its value differences from the neighboring points over the temporal domain, and then creates a vector field representing the prominent changes. Finally, it overlays the vectors along the contour paths, revealing differential trends that the contour lines experienced over time. We evaluated our visualization using real-life datasets, consisting of millions of data points, where the visualizations were generated in less than a minute in a single-threaded execution. Our experimental results reveal that ContourDiff can reliably visualize the differential trends, and provide a new way to explore the change pattern in spatiotemporal data.
ContourDiff:揭示时空数据的差异趋势
时空数据的变化由于其固有的噪声和低变异性(例如,多年来的地质过程)往往不被注意。常用的方法,如并排等高线图和意大利面图,不能清楚地了解这些数据的时间变化。我们提出ContourDiff,这是一种基于矢量的等高线图可视化方法,用于可视化跨越空间区域和时间域的变化趋势。我们的方法首先对每个位置进行聚合,其值与相邻点在时域上的差异,然后创建一个表示突出变化的向量场。最后,它沿着等高线路径叠加矢量,揭示等高线随时间变化的不同趋势。我们使用由数百万个数据点组成的真实数据集来评估我们的可视化,在单线程执行中,可视化在不到一分钟的时间内生成。实验结果表明,ContourDiff可以可靠地将差异趋势可视化,为探索时空数据的变化模式提供了一种新的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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