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  • 标题:Understanding urban infrastructure via big data: the case of Belo Horizonte
  • 本地全文:下载
  • 作者:Aksel Ersoy ; Klaus Chaves Alberto
  • 期刊名称:Regional Studies, Regional Science
  • 印刷版ISSN:2168-1376
  • 电子版ISSN:2168-1376
  • 出版年度:2019
  • 卷号:6
  • 期号:1
  • 页码:1-7
  • DOI:10.1080/21681376.2019.1623068
  • 出版社:Taylor and Francis Ltd
  • 摘要: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.
  • 关键词:infrastructure ; Belo Horizonte ; big data ; interdependency
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