ANNUAL CONGRESS 2025

The Impact of Urban Compactness on the Urban Heat Island Effect - Evidence from 119 Cities in China

Not scheduled

20m

Yildiz Technical University, Istanbul

Oral Track 05 | ENVIRONMENT AND CLIMATE

Speaker

Mr Minghao Zuo (Tianjin University)

Description

In recent years, the ongoing phenomenon of global warming and the frequent occurrence of extreme and unusual weather events have posed significant challenges to the human living environment and public health. Among these challenges, the issue of the urban heat environment has garnered particular attention, as evidenced by the prominence of the urban heat island(UHI) effect in research and discourse. The urban spatial morphology is indicative of the patterns of human production and living activities. These activities can exert an influence on the spatial configuration of land cover and land use, thereby affecting the intensity of the UHI effect(Xian et al., 2021). Existing studies have predominantly focused on the influence of urban micro-region morphology on local climate(Yang et al., 2021), employing district morphology as the primary driver to explain the urban thermal environment. The spatial clustering of thermal clusters (compact hot areas) has been shown to significantly increase the intensity of UHI(Atri et al., 2021). The compact city concept, which is prevalent in China, has further intensified the agglomeration of human activities within cities, resulting in larger urban thermal clusters. Therefore, it is crucial to explore the impact of urban compact morphology on UHI from a more macro perspective. However, there is a lack of compactness-focused explorations in existing studies, and how UHI responds to various urban compactness patterns remains poorly understood. In this study, we selected 119 cities across six major urban agglomerations in China as our research sites. We employed the city clustering algorithm to delineate the urban cluster boundaries and determined the UHI footprint based on the spillover effect of UHI(Liu et al., 2020), to evaluate and analyse the intensity and the spatial distribution characteristics of average SUHI of July in 2014, 2020, 2023 and 2023. Furthermore, urban compactness was measured in terms of the centrality, Landscape Shape Index (LSI), Aggregation Index(AI) and cohesion of urban cluster, the centrality of population and the centrality of green space. By employing two regression models, Random Forest and Geographical Weighted Random Forest, and the Shapley Additive Explanation method, the drivers of SUHI and their spatial heterogeneity were analyzed. The study has the following main findings: (1) The average SUHI exhibited a relatively smooth change in each urban agglomeration during the study period, while their spatial distributions reflected distinct climate-driven patterns, and the SUHI of cities in the subtropical zone was significantly higher than that in other regions; (2) Except for the centrality of population and the LSI and cohesion of urban cluster, the remainder of the urban compactness indicators have significant impacts on SUHI. The increase in AI of urban cluster will evidently enhance SUHI, while the increase in centrality of urban cluster and green space can effectively alleviate SUHI, but the alleviation effect will diminished once a threshold value is exceeded. (3) The result demonstrates substantial spatial heterogeneity in the relationship between urban compactness indicators and SUHI. The AI and centrality of urban cluster in the southwestern cities have a stronger enhancement effect on SUHI, the centrality of green space in the central cities has a stronger mitigating effect on SUHI, and all indicators in the eastern cities have a weaker effect on SUHI. The results provide effective targeted heat-adaptive compact development strategies for cities in different regions.

References

[1]Atri, M., Nedae-Tousi, S., Shahab, S., & Solgi, E., 2021. The Effects of Thermal-Spatial Behaviours of Land Covers on Urban Heat Islands in Semi-Arid Climates. Sustainability. https://doi.org/10.3390/su132413824.
[2]Liu, H., Huang, B., Zhan, Q., Gao, S., Li, R., & Fan, Z., 2021. The influence of urban form on surface urban heat island and its planning implications: Evidence from 1288 urban clusters in China. Sustainable Cities and Society, 71, pp. 102987. https://doi.org/10.1016/J.SCS.2021.102987.
[3]Ming, Y., Liu, Y., Li, Y., & Song, Y., 2024. Unraveling nonlinear and spatial non-stationary effects of urban form on surface urban heat islands using explainable spatial machine learning. Computers, Environment and Urban Systems, Volume 114, pp. 102200. https://doi.org/10.1016/j.compenvurbsys.2024.102200.
[4]Xian, G., Shi, H., Auch, R., Gallo, K., Zhou, Q., Wu, Z., & Kolian, M., 2021. The effects of urban land cover dynamics on urban heat Island intensity and temporal trends. GIScience & Remote Sensing, 58, pp. 501 - 515. https://doi.org/10.1080/15481603.2021.1903282.
[5]Yang, J., Yang, Y., Sun, D., Jin, C., & Xiao, X., 2021. Influence of urban morphological characteristics on thermal environment. Sustainable Cities and Society, 72, pp. 103045. https://doi.org/10.1016/J.SCS.2021.103045.