I. Introduction
The ubiquitous availability of location sensing devices embedded in smartphones, cars, taxis, and other devices, combined with the ability to collect data at scale, enables the fine grained monitoring and modeling of human movement, both at the individual level and at the group level. Using trajectory data harvested by GPS, RFID and mobile devices, complex pattern queries can be posed against objects moving in both time and space. Answering these queries introduces opportunities for business intelligence, where prediction regarding future patterns can be used to solve challenging problems such as traffic congestion prediction, crime pattern analysis and prediction, epidemic spread characterization and alerting, insurance pricing, and targeted advertising. This work focuses on the spatial aspect of spatiotemporal queries.