{"title":"The landscape pattern characteristics of urban built-up land significantly influence urban thermal comfort: Evidence from large cities in China","authors":"Chunguang Hu, Hui Zeng","doi":"10.1016/j.scs.2025.106402","DOIUrl":null,"url":null,"abstract":"<div><div>The rapid convergence of urban development drivers and Thermal Comfort (TC) demands highlights a critical gap in understanding the relationship between the Landscape Pattern Characteristics (LPC) of Urban Built-up Land (UBL) and TC. Using Shapley Additive Explanations (SHAP) within an Interpretable Machine Learning (IML) framework, this study investigates the nonlinear, spatially non-stationary impacts of UBL's LPC on TC. The findings reveal complex spatial interactions: (1) A threshold effect between patch area and TC, with TC sharply declining when the Largest Patch Index (LPI) exceeds 0.65 and the Mean Patch Area (AREA_MN) surpasses 0.2; (2) Patch shape complexity exhibits a significant nonlinear relationship with TC: higher Perimeter-Area Fractal Dimension (PAFRAC > 0.36) and Shape Area Metric (SHAPE_AM > 0.22) increase shape irregularity, enhancing heat retention and negatively impacting TC; (3) Moderate patch aggregation, characterized by Patch Density (PD) > 0.15, can improve TC if inter-patch connectivity, measured by Effective Mesh Size (MESH < 0.1), is sufficiently enhanced; (4) The interaction of area, shape, and aggregation characteristics reveals key regulatory mechanisms, highlighting the positive impact of small-scale, simplified morphologies and reduced fragmentation on TC. These findings provide scientific guidance for urban planning and microclimate regulation.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106402"},"PeriodicalIF":10.5000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670725002781","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The rapid convergence of urban development drivers and Thermal Comfort (TC) demands highlights a critical gap in understanding the relationship between the Landscape Pattern Characteristics (LPC) of Urban Built-up Land (UBL) and TC. Using Shapley Additive Explanations (SHAP) within an Interpretable Machine Learning (IML) framework, this study investigates the nonlinear, spatially non-stationary impacts of UBL's LPC on TC. The findings reveal complex spatial interactions: (1) A threshold effect between patch area and TC, with TC sharply declining when the Largest Patch Index (LPI) exceeds 0.65 and the Mean Patch Area (AREA_MN) surpasses 0.2; (2) Patch shape complexity exhibits a significant nonlinear relationship with TC: higher Perimeter-Area Fractal Dimension (PAFRAC > 0.36) and Shape Area Metric (SHAPE_AM > 0.22) increase shape irregularity, enhancing heat retention and negatively impacting TC; (3) Moderate patch aggregation, characterized by Patch Density (PD) > 0.15, can improve TC if inter-patch connectivity, measured by Effective Mesh Size (MESH < 0.1), is sufficiently enhanced; (4) The interaction of area, shape, and aggregation characteristics reveals key regulatory mechanisms, highlighting the positive impact of small-scale, simplified morphologies and reduced fragmentation on TC. These findings provide scientific guidance for urban planning and microclimate regulation.
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;