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Visualizing Travel Patterns with a GPS Dataset: How Commuting Routes Influence Non-Work Travel Behavior
This paper examines the spatial patterns of non-work activities for 34 drivers in the Southeast Michigan region. Capitalizing upon a unique global positioning systems (GPS) dataset and GIS visualization techniques, this study quantifies the spatial distributions of non-work activities for drivers with different commuting distances, and for non-work activities that are chained in different types of travel (commute travel vs. non-commute travel). We find a strong dependence of non-work activity locations on commuting distances, and an influence of commuting routes on non-work activities chained in all types of travel. The results underline the importance of commuting routes in shaping the spatial configuration of non-work activities.
Visualizing Travel Patterns with a GPS Dataset: How Commuting Routes Influence Non-Work Travel Behavior
This paper examines the spatial patterns of non-work activities for 34 drivers in the Southeast Michigan region. Capitalizing upon a unique global positioning systems (GPS) dataset and GIS visualization techniques, this study quantifies the spatial distributions of non-work activities for drivers with different commuting distances, and for non-work activities that are chained in different types of travel (commute travel vs. non-commute travel). We find a strong dependence of non-work activity locations on commuting distances, and an influence of commuting routes on non-work activities chained in all types of travel. The results underline the importance of commuting routes in shaping the spatial configuration of non-work activities.
Visualizing Travel Patterns with a GPS Dataset: How Commuting Routes Influence Non-Work Travel Behavior
Wang, Xiaoguang (Autor:in) / Grengs, Joe (Autor:in) / Kostyniuk, Lidia (Autor:in)
Journal of Urban Technology ; 20 ; 105-125
01.07.2013
21 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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