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Effects of 2D/3D Urban Morphology on Cooling Effect Diffusion of Urban Rivers in Summer: A Case Study of Huangpu River in Shanghai

Author

Listed:
  • Yuhui Wang

    (Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Shuo Sheng

    (School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China)

  • Junda Huang

    (Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Yuncai Wang

    (Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    Center of Ecological Planning and Environment Effects Research, Joint Laboratory of Ecological Urban Design, Shanghai 200092, China)

Abstract

The diffusion effect of river cooling is critical for mitigating the urban heat island effect in riverside areas and for establishing an urban cooling network. River cooling effect diffusion is influenced by the two-dimensional (2D) and three-dimensional (3D) urban morphology of surrounding areas. However, the characteristics of 2D/3D urban morphology that facilitate efficient river cooling effect diffusion remain unclear. This study establishes a technical framework to analyze river cooling effect diffusion resistance (RCDR) across different urban morphologies, using the Huangpu River waterside area in Shanghai as a case study. Seven urban morphology indicators, derived from both 2D and 3D dimensions, were developed to characterize the river cooling effect diffusion resistance. The relative contributions and marginal effects were analyzed using the Boosted Regression Tree (BRT) model. The study found that (1) river cooling effect diffusion was heterogeneous, with four typical patterns; (2) the Landscape Shape Index (LSI) and Blue-green Space Ratio (BGR) significantly impacted cooling effect diffusion; and (3) optimal cooling effect diffusion occurred when the blue-green space occupancy ratio exceeded 20% and building density ranged from 0.1 to 0.3. This study’s technical framework offers a new perspective on river cooling effect diffusion and heat island mitigation in riverside spaces, with significant practical value and potential for broader application.

Suggested Citation

  • Yuhui Wang & Shuo Sheng & Junda Huang & Yuncai Wang, 2025. "Effects of 2D/3D Urban Morphology on Cooling Effect Diffusion of Urban Rivers in Summer: A Case Study of Huangpu River in Shanghai," Land, MDPI, vol. 14(7), pages 1-23, July.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:7:p:1498-:d:1705509
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    References listed on IDEAS

    as
    1. Yunfang Jiang & Jing Huang & Tiemao Shi & Hongxiang Wang, 2021. "Interaction of Urban Rivers and Green Space Morphology to Mitigate the Urban Heat Island Effect: Case-Based Comparative Analysis," IJERPH, MDPI, vol. 18(21), pages 1-29, October.
    2. Jishu Huang & Yun Wang, 2023. "Research on Social Service Effectiveness Evaluation for Urban Blue Spaces—A Case Study of the Huangpu River Core Section in Shanghai," Land, MDPI, vol. 12(7), pages 1-26, July.
    3. Fadel Muhammad & Changkun Xie & Julian Vogel & Afshin Afshari, 2022. "Inference of Local Climate Zones from GIS Data, and Comparison to WUDAPT Classification and Custom-Fit Clusters," Land, MDPI, vol. 11(5), pages 1-19, May.
    4. Wei Chen & Jianjun Zhang & Xuelian Shi & Shidong Liu, 2020. "Impacts of Building Features on the Cooling Effect of Vegetation in Community-Based MicroClimate: Recognition, Measurement and Simulation from a Case Study of Beijing," IJERPH, MDPI, vol. 17(23), pages 1-22, November.
    5. Zheng Zhao & Huimin Gan & Xin Qian & Jiahui Leng & Yanbin Wang & Peipei Wu, 2021. "Riverside Greenway in Urban Environment: Residents’ Perception and Use of Greenways along the Huangpu River in Shanghai, China," IJERPH, MDPI, vol. 18(3), pages 1-22, January.
    6. Yuanyuan Li & Lina Zhao & Hao Zheng & Xiaozhou Yang, 2025. "Using New York City’s Geographic Data in an Innovative Application of Generative Adversarial Networks (GANs) to Produce Cooling Comparisons of Urban Design," Land, MDPI, vol. 14(7), pages 1-32, July.
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