Discovering Urban Mobility Patterns and Demand for Uses of Urban Spaces from Mobile Phone Data

Abstract

In sustainable urban mobility, the analysis of the daily life of citizens and mobility plans are being developed using data obtained through traditional methods like surveys. However, it is compulsory a new approach to study how citizens are moving in the city. In this context, the Arequipa Smart City research project developed a mobile application to gather geospatial data of the daily mobility of a group of university students. This work aims to discover urban mobility patterns using the information of the displacement data and the urban spaces represented by polygons. An important stage is to clean the data before to process and analyze the student’ mobility data. The analysis of mobility patterns is supported by the duality conditions of space-time. The spatial conditions of the points of interest are analyzed using the geographic location of the students. From this analysis, we understand the demand for the use of urban spaces. Second, the temporal conditions are analyzed using stay time on urban space to discover the frequency of use of urban spaces. The results allow understanding the student's interaction with metropolitan urban spaces. In addition, we discuss the results to explain the importance of the analysis of smart mobility patterns in metropolitan areas to address urban accessibility.

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