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This research proposes that vehicles in an urban setting subject to persistent Intelligence Surveillance and Reconnaissance will exhibit attributes that make it possible to predict their future position within a time-horizon. GeoSpatial Information Systems obtained from municipal, commercial, or hyperspectral sources may be used to model an urban grid and to make use of graph-theoretic search algorithms that can prune the future state-space of the vehicle's immediate environment. The results are representational polygons inside the GIS environment that constrict around the subject's likely destinations in the urban grid as the stream of observations continue to drive the process.