Revealing the impact of urban spatial morphology on land surface temperature in plain and plateau cities using explainable machine learning

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2025-01-01 DOI:10.1016/j.scs.2024.106046

Zi Wang , Rui Zhou , Jin Rui , Yang Yu

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引用次数: 0

Abstract

Rapid urbanization has intensified urban heat island (UHI) effects, highlighting the need to understand UHI drivers to improve local thermal environments. While previous research has shown Urban spatial morphology significantly influences land surface temperature (LST), the mechanisms and characteristics of this impact across different geographic conditions remain unclear. Based on this, we selected the main urban areas of Chengdu and Lhasa as examples, using machine learning models and Shapley additive explanation (SHAP) method to reveal the linear and nonlinear relationships between Urban spatial morphology and LST from a morphological perspective. The results show that: (1) The built environment has the most significant impact on LST in plain cities, while the morphology of green space more strongly regulates LST in plateau cities. (2) Building height and density of core both reflect a role in reducing LST in plateau cities. (3) The interaction mechanisms of building density and building height features show the same trend in both plain and plateau cities. However, density of branch between 0.1 and 0.2 reduces LST in plain cities, while densities below 0.1 are more effective in reducing LST in plateau cities. Our results can provide refined and differentiated references for urban planners dedicated to mitigating UHI.

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来源期刊

Sustainable Cities and Society Social Sciences-Geography, Planning and Development

CiteScore

22.00

自引率

13.70%

发文量

810

审稿时长

27 days

期刊介绍： Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;