Sampling Urban Mobility through On-line Repositories of GPS Tracks

We analyze urban mobility by relying on the short-term mo-bility traces gathered from a publicly available web-based repository of GPS tracks- the Nokia Sports Tracker ser-vice1. All mobility traces are obtained from a set of kml files2. We show how the data collected voluntarily by in-dividuals, equipped with GPS-enabled mobile phones, can be used to infer accurate, large-scale footprint of urban mo-bility. This method, unlike others- for example, personal interviewing, is more scalable and less time consuming. It exploits the fact that the on-line masses are willing to share their experience with others. We present a set of heuristics used to filter out bogus tracks from the dataset. We show that the mobility patterns, inferred from the remaining, credible, short-term mobility traces have macroscopic characteristics similar to the char-acteristics of mobility patterns retrieved from the long-term mobility traces, gathered in different urban environments. The results of our analysis lead to a proposal for creating city-specific mobility profiles. We discuss how such profiles could help improve location privacy and help develop new context-aware applications and services for mobile users