Environmental contextualization of uncertainty for moving objects

Spatiotemporal objects are frequently characterized not only in terms of their position, but also by the uncertainty associated with the measurement of that position. Uncertainty metrics are typically parametric and serve in support of the estimation of probable location for a given object. Unfortunately, this parametric approach fails to model the manner in which the environment influences the movement of a spatiotemporal object and, commensurately, the effect of the environment on uncertainty. This research systematically considers the effect of environmental objects and fields in terms of their influence on movement of spatiotemporal objects. Utilizing a simple ontology of spatiotemporal uncertainty, the manner in which the semantic characteristics of environmental objects serve to contextualize an otherwise purely parametric estimation of spatiotemporal uncertainty is examined. The ontology allows for reallocation of positional probability through the environmental contextualization of each probable point of occurrence and spatial reallocation of the contextualized points via an approach wherein “hindrances” such as buildings serve to repel probability of occurrence, and “enablers” such as roads serve to attract probable occurrences. The demonstrated characterization of uncertainty offers opportunities for increased efficiency with respect to spatiotemporal database queries and the possibility for increased accuracy with regard to the representation of probable historic, current and future trajectories.