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Identify park's use based on clusters of visitors' movements in public open spaces

Roberto Pierdicca, Marina Paolanti, Raffaele Vaira, Ernesto Marcheggiani, Eva Savina Malinverni, Emanuele Frontoni


Planning urban parks is a burdensome task, requiring the knowledge of countless variables that are impossible to take into account at the same time.
One of these variables is the set of people who use the parks.
Despite the huge amount of data available, due to the digital footprints left by individuals using their mobile devices, there is no standardized method which enables landscape planners to use this data to design urban parks.
The objective of this study is to design an approach able to understand how an urban green park is really used by its visitors, so as to provide planners and the managing authorities with such a method.
A trajectory clustering algorithm is used to infer the most common trajectories of the visitors, exploiting GPS and sensor-based tracks. Data Analytic methods based on both massive and clustered user data are exploited to proved automatically insight on Public Open Space user behaviour.
Based these user generated data, the proposed data driven approach can determine the mission of the park by processing visitors' trajectories while using a mobile application specifically designed for this purpose.
Furthermore, the data allow an in depth investigation of other information obtained from the users, which can be useful for planners to design policy for planning a public open space.
Results show the feasibility of the proposed approach on a real test case.

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This work is licensed under a Creative Commons Attribution 3.0 License.