Interactive visualization of multivariate trajectory data with density maps

Roeland Scheepens, N. Willems, H. V. D. Wetering, J. V. Wijk
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引用次数: 118

Abstract

We present a method to interactively explore multiple attributes in trajectory data using density maps, i.e., images that show an aggregate overview of massive amounts of data. So far, density maps have mainly been used to visualize single attributes. Density maps are created in a two-way procedure; first smoothed trajectories are aggregated in a density field, and then the density field is visualized. In our approach, the user can explore attributes along trajectories by calculating a density field for multiple subsets of the data. These density fields are then either combined into a new density field or first visualized and then combined. Using a widget, called a distribution map, the user can interactively define subsets in an effective and intuitive way, and, supported by high-end graphics hardware the user gets fast feedback for these computationally expensive density field calculations. We show the versatility of our method with use cases in the maritime domain: to distinguish between periods in the temporal aggregation, to find anomalously behaving vessels, to solve ambiguities in density maps via drill down in the data, and for risk assessments. Given the generic framework and the lack of domain-specific assumptions, we expect our concept to be applicable for trajectories in other domains as well.
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多变量轨迹数据与密度图的交互式可视化
我们提出了一种使用密度图交互式地探索轨迹数据中的多个属性的方法,即显示大量数据的汇总概述的图像。到目前为止,密度图主要用于可视化单个属性。密度图是通过双向程序创建的;首先将光滑轨迹聚合在密度场中,然后将密度场可视化。在我们的方法中,用户可以通过计算数据的多个子集的密度场来沿着轨迹探索属性。然后,这些密度场要么组合成一个新的密度场,要么先可视化,然后再组合。使用称为分布图的小部件,用户可以以有效和直观的方式交互式地定义子集,并且在高端图形硬件的支持下,用户可以快速获得这些计算成本高昂的密度场计算的反馈。我们通过海事领域的用例展示了我们的方法的多功能性:区分时间聚合中的时间段,发现异常行为的船只,通过深入数据解决密度图中的模糊性,以及进行风险评估。考虑到通用框架和缺乏特定领域的假设,我们希望我们的概念也适用于其他领域的轨迹。
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