A pre-processing and network analysis of GPS tracking data

ABSTRACT

Global Positioning System (GPS) devices afford the opportunity to collect accurate data on unit movements from temporal and spatial perspectives. With a special focus on GPS technology in travel surveys, this paper proposes: (1) two algorithms for the pre-processing of GPS data in order to deal with outlier identification and missing data imputation; (2) a clustering approach to recover the main points of interest from GPS trajectories; and (3) a weighted-directed network, which incorporates the most relevant characteristics of the GPS trajectories at an aggregate level. A simulation study shows the goodness-of-fit of the imputation data algorithm and the robustness of the clustering algorithm. The proposed algorithms are then applied to three cases studies relating to the mobility of cruise passengers in urban contexts.

KEYWORDS:

• cluster-based method
• network analysis
• spatio-temporal data
• global positioning systems

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the invaluable comments of the editor and reviewers. They are also grateful to Professor Szilvia Gyimóthy at the Copenhagen Business School, Department of Marketing; the Department Internationalisation and Tourism at the Municipality of Copenhagen; and the Copenhagen Cruise Network at VisitCopenhagen, Copenhagen, for data collection operations in Copenhagen.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.