Visualization of Dynamics in Linear Referenced Transportation Data

Linear referencing represents locations along routes, linear features with an established measurement system, using relative positions. It allows locating events along routes without segmenting it, and has been applied to manage linear features in transportation and utility. In transportation, dynamics in variant attributes such as speed limit, number of lanes, surface material, and traffic accidents, are often saved in event tables. Although events can be displayed via dynamic segmentation, there are difficulties in handling dynamics or changes in events. For example, it is hard to distinguish multiple resurfacing events over time at one location. When variant attributes are associated, dynamic segmentation split a route into short segments and the display can be greatly slowed down. In this study, I explore alternative approaches, including dynamic segmentation with temporal offset in 2-dimesional (2D) and 3-dimensional (3D) view, and animation for visualization of dynamics in linear referenced transportation data. In the first approach, temporal offset is introduced as a relative time axis. The older an event is, the closer it is to the route. This method works in the same way for one or variant attributes without over-segmentation. Using dynamic segmentation with temporal offset, it is not only fast in visualizing dynamics across different attributes, but also straightforward for visual analysis of the history in transportation data. The 3D view approach treats the time in transportation data as the third dimension in the space. Compared to dynamic segmentation with temporal offset in 2D, the 3D view is better for areas with dense linear features. Dynamics in both 2D and 3D view can be animated. In summary, this study provides alternative visualization for dynamics in linear referenced transportation data. Moreover, these approaches are not limited to transportation data but can be applied toward general dynamics in linear referencing.