ANNUAL CONGRESS 2025

Deciphering Non-linear Correlations Between The Built Environment And Thermal Environment: Empirical Evidence From Zhengzhou, China

Not scheduled

20m

Yildiz Technical University, Istanbul

Oral Track 05 | ENVIRONMENT AND CLIMATE

Speaker

Mr RunLong Gao (Henan Polytechnic University)

Description

Identifying the built-environment characteristics related to the thermal environment is crucial for mitigating climate issues through planning interventions. Existing studies typically use linear regression, which struggles to accurately depict the complex association patterns between the built environment and the thermal environment. Taking the central urban area of Zhengzhou, China as an example, this study uses high-resolution remote-sensing images in summer over several years to precisely analyze the spatiotemporal distribution of the urban thermal environment, and deeply explore the impacts of built-environment factors such as building density, the proportion of green space and water bodies, and road networks on the thermal environment. This study applies Random Forest (RF) and Geographically Weighted Regression (GWR) to reveal the non-linear relationships and spatial variations between the built environment and the thermal environment. The research findings are as follows: the thermal environment in Zhengzhou shows an overall patchy distribution, with a relatively large number of heat cores and a scattered spatial distribution; among the built-environment factors, the open-space ratio and green-space ratio have a negative impact on the surface thermal environment, building density has a positive impact, and the building shape coefficient has a two-way regulatory effect on the surface thermal environment; there are significant differences in the comprehensive impact degrees of various built-environment factors on the thermal environment under different regression model fittings. The results of this study have significant planning implications for proposing practical urban thermal-environment optimization strategies, effectively alleviating the urban heat island effect, and comprehensively optimizing the urban human settlement environment.