The Impacts of Heatwaves on Population Distribution in the Subtropical City: A Case Study of Nanchang, China

Zixun Chen and Zongcai Wei ()
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Zixun Chen: School of Architecture, South China University of Technology, Guangzhou 510640, China
Zongcai Wei: State Key Laboratory of Subtropical Building and Urban Science, Guangzhou 510640, China

Land, 2025, vol. 14, issue 6, 1-25

Abstract: Global warming has intensified the frequency and intensity of heatwaves, particularly in urban areas, significantly affecting residents’ daily activities. Extant studies have mainly concentrated on the relationship between socio-economic attributes and the impacts of heatwaves on urban populations. However, the relationship between the built environment and the impacts of heatwaves on urban population distribution has not received much attention. Furthermore, most studies have overlooked the temporal heterogeneity in heatwave impacts on population activities and distribution. Therefore, taking the central urban area of Nanchang as the case, this study investigated the impacts of heatwaves on population distribution and their temporal heterogeneity. Moreover, it identified the nonlinear relationships between built environment factors and population changes during heatwaves by using the XGBoost model and SHAP method. The results revealed that heatwaves exerted the largest impacts on population distribution during weekend nights, followed by weekend daytime and weekday nighttime, with the least impacts observed during weekday daytime. Furthermore, location and transportation factors significantly affected population changes during heatwaves across most time periods, with their influences being associated with policy factors such as the high-temperature leave policy for workers in industrial zones located in urban fringe areas and the cooling zone establishment policy for citizens in subway stations. Moreover, land use and building form factors exhibited significant temporal heterogeneity in their impacts on population changes during heatwaves. This temporal heterogeneity was fundamentally driven by individuals’ heat adaptation behaviors, the spatiotemporal patterns of their daily activities, and the diurnal variations in the built environment’s influence on local thermal environment. These findings provide valuable insights to proactively alleviate the adverse impacts of heatwaves.

Keywords: heatwave; population distribution; temporal heterogeneity; built environment; population heatmap; machine learning (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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