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  • 标题:Big Data-Driven Urban Management: Potential for Urban Sustainability
  • 本地全文:下载
  • 作者:Min Wu ; Bingxin Yan ; Ying Huang
  • 期刊名称:Land
  • 印刷版ISSN:2073-445X
  • 出版年度:2022
  • 卷号:11
  • 期号:5
  • 页码:680
  • DOI:10.3390/land11050680
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:With the world’s rapidly growing urbanization, urban sustainability is now expected for urban life. Due to this rapid growth, meeting the emerging challenges for urban management and sustainability worldwide is challenging. Big data-driven technologies can be an excellent solution to address these upcoming challenges. Therefore, this study explores the potential of big data technologies for ensuring sustainability in urban management. The study conducted a systematic literature review guided by PRISMA (preferred reporting items for systematic review and meta-analysis) on publications over the last 21 years. The study argues that urban management is an integrated function of public and private agencies to address the significant challenges of urban life and to develop the city as more competitive, habitable, and sustainable. Urban management can utilize big data analytics (BDA) for digital instrumentation, data-informed policy decisions, governance, real-time management, and evidence-based decisions. Urban sustainability can ensure the smooth operation of urban affairs through strategic planning under three major dimensions: social, economic, and environmental. Big data technologies can ensure smart transport, traffic, waste management, energy, environment, infrastructure, safety, healthcare, planning, and citizen participation in regular urban affairs to provide a better urban life. This study develops several indicators that will be helpful for concerned stakeholders in policy, planning, designing, and implementing sustainable urban development.
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