Compact visualization techniques such as dense pixel displays find application in displaying spatio-temporal 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.

紧凑的可视化技术（例如密集像素显示）可用于以节省空间的方式显示时空数据集。虽然主要关注特征开发，但在这些技术中对移动者空间分布的描述通常与更好的可扩展性相对于移动对象的数量。我们提出了 SpatialRugs，这是一种技术，可用于通过应用 2D 颜色图来确定对象位置，从而在此类方法中重新引入空间位置，并使用户即使在非空间表示中也能跟踪时空发展。针对集体运动数据集，我们评估了几种彩色地图的适用性并讨论了局限性。为了减轻感知伪影，我们还介绍并评估了一种自定义的、时间感知的颜色平滑方法。