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Addressing Global Climate Change With Big Data-Driven Urban Planning Policy

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  • John Zacharias

    (Peking University, China)

Abstract

Cities in China gather data to support strategic and operational management, including databases on buildings, land use, human occupancy, underground services, and travel surveys. However, these data are seldom used to analyze policy decisions, with urban planning confined largely to operational planning. Real estate and financial interests dominate strategic planning, while an ecological crisis threatens urban sustainability in the long run. In this research, carbon emissions (CE) related to planning, building, and intra-urban travel are measured for two representative types of typical urban development in southern China, using data from Shenzhen. The two types are contemporary planned units (PUD) and dense, low-rise developments (VSD). It is found that VSD accounts for less than one-third the CE of PUD, although there is considerable diversity in the performance of PUD. Based on this research, major reductions in CE can be achieved by focussing urban planning policy on carbon-efficient development.

Suggested Citation

  • John Zacharias, 2021. "Addressing Global Climate Change With Big Data-Driven Urban Planning Policy," International Journal of E-Planning Research (IJEPR), IGI Global, vol. 10(4), pages 1-16, October.
    • Handle: RePEc:igg:jepr00:v:10:y:2021:i:4:p:1-16
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    References listed on IDEAS

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    2. Wann-Ming Wey & Wei Huang, 2019. "An Integrated Approach For Building A Sustainable City Development Assessment Model," Proceedings of International Academic Conferences 9812128, International Institute of Social and Economic Sciences.
    3. Huang, Ying & Liao, Cuiping & Zhang, Jingjing & Guo, Hongxu & Zhou, Nan & Zhao, Daiqing, 2019. "Exploring potential pathways towards urban greenhouse gas peaks: A case study of Guangzhou, China," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
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    Cited by:

    1. Jiahang Lu & Xiaohua Wu, 2022. "Research on Urban Greenway Alignment Selection Based on Multisource Data," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    2. Fabio De Felice & Antonella Petrillo, 2021. "Green Transition: The Frontier of the Digicircular Economy Evidenced from a Systematic Literature Review," Sustainability, MDPI, vol. 13(19), pages 1-26, October.

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