This chapter explores the potential of mobile phone data in reading urban practices and rhythms of usage of the contemporary city. Presenting the results of two researches, promoted by Telecom Italia and carried out by the authors, the chapter will show how new maps based on mobile phone data analysis can represent spatialized urban practices, providing new insights into space-time patterns of mobility practices. Mobile traffic data employed in the analysis of complex temporal and spatial patterns (Erlang, and origin–destination matrices) were treated as the effect of individual behaviours and habits, offering information about the features of usage of urban spaces that vary over time. Thanks to the processing of mobile phone data, it was possible to describe the intensity of use of the city (during the day, weekdays/holidays, seasons), linking them to the differences in the distribution of urban activities at different hours, day and weeks, as a useful tool to define urban policies regarding the supply of services; managing large and special events (inflow, outflow, monitoring), also estimating the mobility demand and the spatial-temporal variation in population density; describing time-dependent phenomena that are missing from traditional analysis; as well as tracing ‘fuzzy boundaries’ as perimeters of practices, as a tool for supporting and increasing the efficiency of urban policies and mobility services.

Mobile Phone Data in Reading Mobility Practices.

MANFREDINI, FABIO;PUCCI, PAOLA;TAGLIOLATO ACQUAVIVA D'ARAGONA, PAOLO
2016

Abstract

This chapter explores the potential of mobile phone data in reading urban practices and rhythms of usage of the contemporary city. Presenting the results of two researches, promoted by Telecom Italia and carried out by the authors, the chapter will show how new maps based on mobile phone data analysis can represent spatialized urban practices, providing new insights into space-time patterns of mobility practices. Mobile traffic data employed in the analysis of complex temporal and spatial patterns (Erlang, and origin–destination matrices) were treated as the effect of individual behaviours and habits, offering information about the features of usage of urban spaces that vary over time. Thanks to the processing of mobile phone data, it was possible to describe the intensity of use of the city (during the day, weekdays/holidays, seasons), linking them to the differences in the distribution of urban activities at different hours, day and weeks, as a useful tool to define urban policies regarding the supply of services; managing large and special events (inflow, outflow, monitoring), also estimating the mobility demand and the spatial-temporal variation in population density; describing time-dependent phenomena that are missing from traditional analysis; as well as tracing ‘fuzzy boundaries’ as perimeters of practices, as a tool for supporting and increasing the efficiency of urban policies and mobility services.
Understanding Mobilities for Designing Contemporary Cities,
9783319225777
Erlang mobile phone data Origin/destination mobile data Treelet approach Daily practices Urban policy
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/973961
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