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Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats

Author

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  • Juan Shan
  • Zhuo Huang
  • Sibo Chen
  • Yue Li
  • Wenli Ji
  • Zhihan Lv

Abstract

The fast urban development leads to many complex problems. A smart city aims to solve these problems using scientific approaches. Urban Green Space (UGS) is a fundamental component of urban infrastructure. It needs to be upgraded simultaneously with the concept of the smart city. Methods of smart UGS planning and sustainable landscape design help integrate ecological performance and other functions of UGS. Smart UGS planning is a technical management tool and a human-centered smart application. A novel UGS classification method based on function combinations is proposed in the present work. Five types of UGS (Scenic UGS, Residential UGS, Commercial UGS, Office UGS, and Road UGS) in Baqiao District of Xi’an, Shaanxi Province, are selected as sample sites. Interviewees’ socio-economic attributes, visiting frequencies, and differences in demands are investigated. Eventually, the UGSs researched in this work are optimized based on public preferences and the current conditions of the sites. Results demonstrate the following. (1) The public’s preference for different types of UGS is different considerably. (2) Based on the public’s preference, Scenic UGS is improved in terms of quantity, function, and management; Residential UGS is upgraded regarding quantity and accessibility; and Commercial UGS, Office UGS, and Road UGS are improved in terms of quality. The results could provide methodological references for planning different types of UGS and innovative insights for smart UGS planning and sustainable landscape design.

Suggested Citation

  • Juan Shan & Zhuo Huang & Sibo Chen & Yue Li & Wenli Ji & Zhihan Lv, 2021. "Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats," Complexity, Hindawi, vol. 2021, pages 1-10, June.
  • Handle: RePEc:hin:complx:5086636
    DOI: 10.1155/2021/5086636
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    Cited by:

    1. MariaElena Menconi & Rosaria Abbate & Luca Simone & David Grohmann, 2023. "Urban Green System Planning Insights for a Spatialized Balance between PM 10 Dust Retention Capacity of Trees and Urban Vehicular PM 10 Emissions," Sustainability, MDPI, vol. 15(7), pages 1-17, March.
    2. Liqing Zhang & Yue Wu, 2022. "Negative Associations between Quality of Urban Green Spaces and Health Expenditures in Downtown Shanghai," Land, MDPI, vol. 11(8), pages 1-18, August.
    3. Shuhui Yu & Xin Guan & Junfan Zhu & Zeyu Wang & Youting Jian & Weijia Wang & Ya Yang, 2023. "Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China," Sustainability, MDPI, vol. 15(11), pages 1-14, June.

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