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Situational awareness (SA) applications monitor the real world and the entities therein to support tasks such as rapid decision-making, reasoning, and analysis. Raw input about unfolding events may arrive from variety of sources in the form of sensor data, video streams, human observations, and so on, from which events of interest are extracted. Location is one of the most important attributes of events, useful for a variety of SA tasks. In this paper, we propose an approach to model anddoi:10.1145/1183471.1183494 dblp:conf/gis/KalashnikovMMHB06 fatcat:hztuxptocnefjiuxz7fjafwgiu