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Exploring cellular network handover information for urban mobility analysis

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  • Demissie, Merkebe Getachew
  • Correia, Gonçalo Homem de Almeida
  • Bento, Carlos

Abstract

The progressive trend of urbanization involving changes in the activities of a city has created several problems. Addressing these problems requires reliable and detailed information regarding the urban structure and its dynamics. Previous studies have tried to explore cellular networks data for urban analysis, yet little attention has been given in exploring mobility related events of cellular networks. This study uses handover, which is the process of transferring an ongoing call from one cell to the other, to capture urban dynamics. The handover data was collected from cellular towers in Lisbon, Portugal. First, our method started with a pre-processing of the handover data. Then, experiments were carried out to understand the city dynamics through GIS visualization and statistical analysis. The visualizations provided a qualitative explanation of how the movement of calls is useful in highlighting the flow of people in urban infrastructures. Using statistical analysis, two important relationships were proved: there is a significant association between cell towers with a high number of incoming handovers and a high presence of people in their vicinity; and a greater proximity to the main road links of cell towers characterized by a high number of incoming as well as outgoing handovers thus towers denoting more movement. Our results suggest that the handover information, taking the advantage of its pervasiveness, can provide ways to analyze city dynamics at a larger scale. This approach complements the effort of traditional urban data collection methods, which are usually made available less frequently to urban planners and policy makers.

Suggested Citation

  • Demissie, Merkebe Getachew & Correia, Gonçalo Homem de Almeida & Bento, Carlos, 2013. "Exploring cellular network handover information for urban mobility analysis," Journal of Transport Geography, Elsevier, vol. 31(C), pages 164-170.
    • Handle: RePEc:eee:jotrge:v:31:y:2013:i:c:p:164-170
    DOI: 10.1016/j.jtrangeo.2013.06.016
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    References listed on IDEAS

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    1. Emmanouil Tranos & Aura Reggiani & Peter Nijkamp, 2013. "Accessibility of Cities in the Digital Economy," Tinbergen Institute Discussion Papers 13-160/VIII, Tinbergen Institute.
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    3. Correia, Gonçalo & Viegas, José Manuel, 2011. "Carpooling and carpool clubs: Clarifying concepts and assessing value enhancement possibilities through a Stated Preference web survey in Lisbon, Portugal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 81-90, February.
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    1. Barbosa, Samuel Borges & Ferreira, Marcelo Gitirana Gomes & Nickel, Elton Moura & Cruz, Jorge Alcides & Forcellini, Fernando Antônio & Garcia, Jéssica & Guerra, José Baltazar Salgueirinho Osório de An, 2017. "Multi-criteria analysis model to evaluate transport systems: An application in Florianópolis, Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 1-13.
    2. Claudio Gariazzo & Armando Pelliccioni & Maria Paola Bogliolo, 2019. "Spatiotemporal Analysis of Urban Mobility Using Aggregate Mobile Phone Derived Presence and Demographic Data: A Case Study in the City of Rome, Italy," Data, MDPI, vol. 4(1), pages 1-25, January.
    3. Yu, Chang & He, Zhao-Cheng, 2017. "Analysing the spatial-temporal characteristics of bus travel demand using the heat map," Journal of Transport Geography, Elsevier, vol. 58(C), pages 247-255.

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