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Understanding urban infrastructure via big data: the case of Belo Horizonte

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  • Aksel Ersoy
  • Klaus Chaves Alberto

Abstract

One major impact of the global economic crisis is the way it has deepened inequalities around the world. Infrastructure remains essential within this debate as it provides wider health, economic and environmental benefits for society beyond the conventional calculations of cash returns. With the potential exploration of big data, cities now face challenges as well as opportunities to use a series of static and dynamic datasets. Big data methods are offering new opportunities to design decision-making models for urban planning and management. The combination of social media, census, sensors and traditional data gives a new perspective to solve modern urban challenges through a holistic and inclusive approach. Nevertheless, the BOLD methods are relatively new and have not been applied in the context of urban infrastructure. This paper explores whether BOLD methods can help one reconceptualize urban infrastructure not only with technical and operational characteristics but also with social values in the context of the Global South. To demonstrate, Belo Horizonte, Brazil, is used as a case study.

Suggested Citation

  • Aksel Ersoy & Klaus Chaves Alberto, 2019. "Understanding urban infrastructure via big data: the case of Belo Horizonte," Regional Studies, Regional Science, Taylor & Francis Journals, vol. 6(1), pages 374-379, January.
  • Handle: RePEc:taf:rsrsxx:v:6:y:2019:i:1:p:374-379
    DOI: 10.1080/21681376.2019.1623068
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    Cited by:

    1. Min Wu & Bingxin Yan & Ying Huang & Md Nazirul Islam Sarker, 2022. "Big Data-Driven Urban Management: Potential for Urban Sustainability," Land, MDPI, vol. 11(5), pages 1-16, May.
    2. Ayyoob Sharifi & Zaheer Allam & Bakhtiar Feizizadeh & Hessam Ghamari, 2021. "Three Decades of Research on Smart Cities: Mapping Knowledge Structure and Trends," Sustainability, MDPI, vol. 13(13), pages 1-23, June.

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