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This book explains the potential value of using mobile phone data to monitor urban practices and identify rhythms of use in today’s cities. Drawing upon research conducted in the Italian region of Lombardy, the authors demonstrate how maps based on mobile phone data, which are better tailored to the dynamic processes at work in cities, can document urban practices, provide new insights into spatial and temporal patterns of mobility, and assist in recognizing different communities of practice. The described methodology permits detailed visualization of the spatial distribution of mobility flows and offers a more extensive and refined description of the distribution of urban activity than is provided by traditional travel surveys. The book also details how maps derived by processing mobile phone data can assist in the definition of urban policies that will deliver services that match cities’ needs, facilitate the management of large events (inflow, outflow, and monitoring), and reflect time-dependent phenomena not included in traditional analyses.



Chapter 1. Mobility Practices and Mobile Phone Data

This chapter introduces the debate on the role of spatial mobility in describing and assessing urban changes. In accordance with the practice in an established literature, the role of mobility will be discussed as a key for describing the forms and the extent of different life practices and consumption patterns, producing diversified uses of the city. This is a necessary framework for an understanding of the challenges that the new

data sources

Data sources

—such as mobile phone data—have to meet in order to interpret users’ practices and behaviours, described in the realm of mobility. In fact, descriptions of the different social dimensions highlighted by mobility practices call for new empirical and analytical approaches, able to better capture people’s movements, variation in them over time and space, and the multi-sited nature of the activities. In this context, we will investigate the contribution that tracking



and mobile phone network data have to offer. Because analysis of the



variability of

urban practices

Urban practices

is difficult to achieve with

traditional data

Traditional data

sources, our focus will be on the opportunities and limits of mobile phone data in mapping the spatial dimension and the density of use of the city and its




Paola Pucci, Fabio Manfredini, Paolo Tagliolato

Chapter 2. Mobile Phone Data to Describe Urban Practices: An Overview in the Literature

This chapter focuses on the potentialities offered by mobile phone data in reading the site practices and



of usage of the contemporary city, providing a research framework of the most promising approaches. Research approaches using ICT and aggregated cellular network log files to identify fine-grained variations in urban movements are presented to argue how mobile phone data can be treated as a useful source of information on the real use of cities. Because of the pervasiveness guaranteed by the ubiquity of mobile phone networks, this chapter shows how these datasets can overcome limitations in the detection of latency, typical of

traditional data

Traditional data


Data sources

, while also providing valuable information on temporary

urban populations

Urban population

. Referring to the outcomes of research on passive and anonymous monitoring of cell phone traffic (i.e.

Social Positioning Method

Social positioning method

, Mobile Landscape and Real Time Monitoring, Automated

Land Use

Land use

Identification), we illustrate the potential and the challenges of these data source in complementing more traditional




Paola Pucci, Fabio Manfredini, Paolo Tagliolato

Chapter 3. Daily Mobility Practices Through Mobile Phone Data: An Application in Lombardy Region

Beginning with the results of a research carried out in the Italian region of Lombardy utilising mobile phone data provided by Telecom Italia, this chapter will demonstrate how new



, based on mobile phone data and better tailored to the dynamic processes taking place, can represent spatialized urban practices and origin-destination



of daily movements. Three different types of mobile phone data were employed in the analysis of complex temporal and spatial patterns. The first data type concerns the mobile phone traffic registered by the network over the entire

Lombardy Region

Lombardy region

(Northern Italy). Data are expressed in Erlang, a measure of the density of calls. The second typology of data consists in localized and aggregated tracks of anonymized mobile phone



. It is an origin-destination datum derived from the Call Detail Record database. The third type of data refers to the mobile switching centre (MSC), which is the primary service delivery node for GSM, responsible for routing voice calls and text messages. With the maps based on the processing of the three types of mobile phone data, it was possible to offer information on

temporary populations

Temporary population

and city usage patterns (daily/nightly practices, non-systematic mobility).

Paola Pucci, Fabio Manfredini, Paolo Tagliolato

Chapter 4. Implications for Traditional Data Sources

This chapter focuses on the differences between mobile and conventional data sources and illustrates how the former open new implications for the urban research community which needs to elaborate new strategies to integrate user-generated data with traditional data to achieve a better understanding of urban usages, in time and in space. In particular, the main differences lie in the characteristics of the data and the dimension of the samples: conventional data are public and refer to the “universe” of population, mobile phone data are collected by private companies and refer to a subsample of the overall mobile phone subscriptions (i.e. active users). Official statistics are necessary to interact with these new data sources in order to evaluate if, and if so how mobile phone data can be used as new sources, able to describe phenomena for which official statistics do not collect data, as additional sources to be used as complement to conventional data sources or as alternative sources able to replace conventional ones. In this general context, the real challenge for urban studies is integration of the available databases together with an innovative use of traditional sources, in order to capture the variety of changes in urban practices.

Paola Pucci, Fabio Manfredini, Paolo Tagliolato

Chapter 5. Implications for Urban and Mobility Policy

This chapter illustrates the potentiality of mobile phone traffic data for improving the effectiveness of urban policies. Mobile phone traffic data, as the effect of individual behaviour and habits, help in formulating policies more in keeping with the molecular daily practices and emerging demands being made by diverse populations using the city and its services, at varying



and intensities. By offering new maps of site practices and information on temporary populations, the processing of mobile phone data has an important role to play in both the analytical and the normative dimensions of urban policies, within two different perspectives. The first regards the opportunity to use a real-time knowledge of mobility needs, possible through a more widespread use of networked technologies, as a framework for area-wide implementation of innovative

urban policy

Urban policy

and transport supply. The second perspective concerns the valuable support offered by mobile phone data in “re-scaling” urban policy and assisting in the construction of geographies of partnerships between different stakeholders.

Paola Pucci, Fabio Manfredini, Paolo Tagliolato


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