Exploring Human Mobility Patterns Based on Location Information of US Flights
2011 (English)Article in journal (Other academic) Submitted
A range of early studies have been conducted to illustrate human mobility patterns using differenttracking data, such as dollar notes, cell phones and taxicabs. Here, we explore human mobility patternsbased on massive tracking data of US flights. Both topological and geometric properties are examinedin detail. We found that topological properties, such as traffic volume (between airports) and degree ofconnectivity (of individual airports), including both in- and outdegrees, follow a power lawdistribution but not a geometric property like travel lengths. The travel lengths exhibit an exponentialdistribution rather than a power law with an exponential cutoff as previous studies illustrated. Wefurther simulated human mobility on the established topologies of airports with various movingbehaviors and found that the mobility patterns are mainly attributed to the underlying binary topologyof airports and have little to do with other factors, such as moving behaviors and geometric distances.Apart from the above findings, this study adopts the head/tail division rule, which is regularity behindany heavy-tailed distribution for extracting individual airports. The adoption of this rule for dataprocessing constitutes another major contribution of this paper.
Place, publisher, year, edition, pages
scaling of geographic space, head/tail division rule, power law, geographic information, agent-based simulations
IdentifiersURN: urn:nbn:se:kth:diva-89101OAI: oai:DiVA.org:kth-89101DiVA: diva2:502693
QS 201203162012-02-142012-02-142012-11-13Bibliographically approved