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Nowadays large amounts of GPS trajectory data is being continuously collectedby GPS-enabled devices such as vehicles navigation systems and mobile phones.GPS trajectory data is useful for applications such as traffic management,location forecasting, and itinerary planning. Such applications often need toextract the time-stamped Sequence of Visited Locations (SVLs) of the mobileobjects. The nearest neighbor query (NNQ) is the most applied method forlabeling the visited locations based on the IDs of the POIs in the process ofSVL generation. NNQ in some scenarios is not accurate enough. To improve thequality of the extracted SVLs, instead of using NNQ, we label the visitedlocations as the IDs of the POIs which geometrically intersect with the GPSobservations. Intersection operator requires the accurate geometry of thepoints of interest which we refer to them as the Geometries of Interest (GOIs).In some application domains (e.g. movement trajectories of animals), adequateinformation about the POIs and their GOIs may not be available a priori, orthey may not be publicly accessible and, therefore, they need to be derivedfrom GPS trajectory data. In this paper we propose a novel method forestimating the POIs and their GOIs, which consists of three phases: (i)extracting the geometries of the stay regions; (ii) constructing the geometryof destination regions based on the extracted stay regions; and (iii)constructing the GOIs based on the geometries of the destination regions. Usingthe geometric similarity to known GOIs as the major evaluation criterion, theexperiments we performed using long-term GPS trajectory data show that ourmethod outperforms the existing approaches.

Geometry of Interest (GOI): Spatio-Temporal Destination Extraction and Partitioning in GPS Trajectory Data