| Geospatial lifelines capture individuals' locations in geographic space at regular or irregular temporal intervals. With the theoretical foundations provided by Hägerstrand's time geography, lifelines focus on representational, operational, and computational concerns in a geographic information system (GIS). In this study, the lifelines are considered as high-level objects made of tightly bound parts: space and time. Based on the analysis of two kinds of movements, this study proposes two subclasses of lifelines: continuous lifelines and discrete lifelines. It then identifies the attributes and behaviors of lifeline class and the relationships among lifeline objects. This study also proposes an operational framework in which lifeline objects and other spatial objects can be organized and analyzed in an information system setting.; In order to facilitate spatiotemporal proximity and set operations, this study puts forward two hierarchical tree data structures for lifelines, which are especially useful for performing spatioternporal analysis under different scales. In addition, this study investigates a quantitative approach to the calculation of the potential path area of lifelines at any time instants, and conducts an empirical study regarding the maximum potential stop time of continuous lifelines.; The detection of “hot spots” provides an effective avenue for exploring spatial data. Space-time lifelines attach them with new meanings and pose new challenges due to the complex multidimensional nature and the staggering computational demands. This study summarizes the different kinds of “hot spots” in a space-time context, and proposes the ways of adaptation of existing “hot spots” detection techniques for lifelines. The results of this study show that applying the conventional “hot spots” detection techniques to the lifelines may lead to erroneous conclusions if based on a snapshot view of longitudinal data. The space-time “hot spots” detection, while allows us to discover the real important agents in the spatiotemporal processes, tends to be sensitive to the control parameters.; Visualization technologies play an important role in quantitative reasoning. This study discusses the peculiarities of geospatial lifeline data which cause many of the problems for lifeline visualization, explores some of the visualization techniques that may be applied for lifelines, and provides several alternative visualization techniques. |
