SpatialRugs: A compact visualization of space and time for analyzing collective movement data

被引:6
作者
Buchmueller, Juri F. [1 ]
Schlegel, Udo [1 ,2 ]
Cakmak, Eren [1 ]
Keim, Daniel A. [1 ]
Dimara, Evanthia [1 ,3 ]
机构
[1] Univ Konstanz, Univ Str 10,POB 78, D-78457 Constance, Germany
[2] Untangle AI, Singapore, Singapore
[3] Univ Utrecht, Utrecht, Netherlands
来源
COMPUTERS & GRAPHICS-UK | 2021年 / 101卷
关键词
Computers and graphics; Information visualization; Collective behavior visualization; Spatiotemporal data; VISUAL EXPLORATION; PREDICTION; ANALYTICS; IMAGE;
D O I
10.1016/j.cag.2021.08.003
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Compact visualization techniques such as dense pixel displays find application in displaying spatiotemporal datasets in a space-efficient way. While mostly focusing on feature development, the depiction of spatial distributions of the movers in these techniques is often traded against better scalability towards the number of moving objects. We propose SpatialRugs, a technique that can be applied to reintroduce spatial positions in such approaches by applying 2D colormaps to determine object locations and which enables users to follow spatio-temporal developments even in non-spatial representations. Geared towards collective movement datasets, we evaluate the applicability of several color maps and discuss limitations. To mitigate perceptional artifacts, we also present and evaluate a custom, time-aware color smoothing method. (C) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页码:23 / 34
页数:12
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