Optimizing Public Space Quality in High-Density Old Districts of Asian Megacities: Thermal Environment Analysis of Shenzhen’s Urban Fringe

High density old districts at the urban fringes of Asian megacities, such as Shenzhen, face significant thermal challenges due to dense building clusters, limited airflow, and heat retention. This study adopts an integrated approach combining Phoenics wind simulation, geographic information system (GIS) modeling, and spatial prototype analysis to assess and optimize the wind and thermal environments in these urban areas. It investigates how spatial configurations, including building density, height distribution, orientation, and green space integration, influence wind flow and thermal comfort. The results demonstrate that optimized spatial arrangements, including reduced building density, height adjustments, and strategic landscape design, improve ventilation and temperature regulation. Comparative analyses of different spatial prototypes reveal that radial configurations effectively channel external winds into the urban core, enhancing internal airflow, whereas rectangular layouts create wind shadows that hinder ventilation. Adjustments to building façades and vertical arrangements further mitigate pedestrian-level heat accumulation. Interventions in public spaces, including green roofs and vertical greening, offer cooling benefits and mitigate urban heat island effects. This study underscores the importance of aligning urban design with natural wind flow and offers a framework for sustainable landscape and architectural strategies in high-density, heat-prone environments. The findings offer valuable insights for urban planners and policymakers seeking sustainable development in similar megacities.

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Publication Details

Journal
Buildings
Published
2025-06-21
DOI
https://doi.org/10.3390/buildings15132166
Citations
1
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
1.30
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article

Optimizing Public Space Quality in High-Density Old Districts of Asian Megacities: Thermal Environment Analysis of Shenzhen’s Urban Fringe

Xiaohui Xu, Jie Ren, Jin Ming Jiang
1 citations
Buildings
Remote Sensing and Land Use
1.30
article

Optimizing Public Space Quality in High-Density Old Districts of Asian Megacities: Thermal Environment Analysis of Shenzhen’s Urban Fringe

Xiaohui Xu, Jie Ren, Jin Ming Jiang
article en
1 citations

Abstract

High density old districts at the urban fringes of Asian megacities, such as Shenzhen, face significant thermal challenges due to dense building clusters, limited airflow, and heat retention. This study adopts an integrated approach combining Phoenics wind simulation, geographic information system (GIS) modeling, and spatial prototype analysis to assess and optimize the wind and thermal environments in these urban areas. It investigates how spatial configurations, including building density, height distribution, orientation, and green space integration, influence wind flow and thermal comfort. The results demonstrate that optimized spatial arrangements, including reduced building density, height adjustments, and strategic landscape design, improve ventilation and temperature regulation. Comparative analyses of different spatial prototypes reveal that radial configurations effectively channel external winds into the urban core, enhancing internal airflow, whereas rectangular layouts create wind shadows that hinder ventilation. Adjustments to building façades and vertical arrangements further mitigate pedestrian-level heat accumulation. Interventions in public spaces, including green roofs and vertical greening, offer cooling benefits and mitigate urban heat island effects. This study underscores the importance of aligning urban design with natural wind flow and offers a framework for sustainable landscape and architectural strategies in high-density, heat-prone environments. The findings offer valuable insights for urban planners and policymakers seeking sustainable development in similar megacities.

BuildingsVol. 15(13)
Sichuan Fine Arts Institute (CN)
Openalex Percentile: Top 21%
Remote Sensing and Land Use
1.30
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