Density-based Algorithm and Network Analysis for GPS Data

The use of advanced global positional system (GPS) trackers has emerged as a novel technology in data collection of units movements. GPS data contain alarge amount of information since the signals of the units are recorded almost in real time. The analysis of GPS data can be carried on several aspects of the spatial movements. In this study, we focus on statistical methods for the identification of points of interests and the analysis of the network of movements for GPS data.In particular, a density cluster-based algorithm is applied to summarize the vast amount of information and to find the most relevant points of attractions. A directednetwork synthesizes the individual unit path by using the latter information. Finally, we aggregate the unit paths in a weighted directed network which is studied throughnetwork analysis. We apply the proposed approach to a case study on cruise passengers’ movements in an urban context.