GIScience 2012: Geographic Information Science pp 43-56 | Cite as
Context-Aware Similarity of Trajectories
Conference paper
Abstract
The movement of animals, people, and vehicles is embedded in a geographic context. This context influences the movement. Most analysis algorithms for trajectories have so far ignored context, which severely limits their applicability. In this paper we present a model for geographic context that allows us to integrate context into the analysis of movement data. Based on this model we develop simple but efficient context-aware similarity measures. We validate our approach by applying these measures to hurricane trajectories.
Keywords
Movement data geographic context similarity measuresPreview
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