Dynamic Time Transformations for Visualizing Multiple Trajectories in Interactive Space-time Cube

Space-time cube is a visualization technique representing (geographic) space and time by three display dimensions. This technique is used to visualize and explore trajectories of moving objects. However, it may be ineffective when the number of different trajectories is large and/or the time span of the data is long. We overcome the limitations in two complementary ways: first, clustering of trajectories by spatial similarity, and, second, transformation of the temporal references within the trajectories to facilitate comparisons within and between clusters. We demonstrate the work of the approach on a real data set about individual movement over one year. INTRODUCTION Interactive space-time cube (STC) has become a common technique for visualizing trajectories (Kraak 2003, Kapler and Wright 2005). STC can support comparison of spatial, temporal, and dynamic properties of several trajectories when they are close in time (dynamic properties include the speed profile over time and stops occurring on the way). However, exploration of a large number of trajectories distributed over a long time period is not effectively supported. One of the problems is visual clutter resulting from numerous intersections of lines representing spatially dissimilar trajectories. Another problem is that trajectories distant in time are hard to compare since the lines representing them are distant in the cube. The problems are illustrated below.