Heat stress resilience assessment of urban form from physical space dimension: A case study of Guangdong-Hong Kong-Macao Greater Bay Area

Improving urban resilience is crucial to counteract rising high-temperature disasters. This study constructed a framework for a process-based heat stress resilience (HSR_phy) assessment from the urban physical space dimension. Based on the universal thermal climate index (UTCI), the Weather Research and Forecasting (WRF) model, and the Local Climate Zone (LCZ) map generated through WUDAPT, an HSR_phy evaluation method with high spatiotemporal accuracy is proposed. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was studied for heat stress resilience patterns in July 2021. Boosted regression tree (BRT) models analyzed LCZ landscape patterns' impacts on HSR_phy. The results indicated that HSR_phy during the daytime was significantly lower than that at night. The HSR_phy of GBA showed the characteristics of low inland and high periphery. Significant differences in HSR_phy existed among most LCZs. LCZA, LCZC, and LCZ9 showed strong HSR_phy, whereas LCZ2, LCZ8, and LCZ7 were opposite. At the 1500 m scale, the Percentage of Landscape (PLAND), Landscape Shape Index (LSI), and Shannon's Diversity Index (SHDI) of LCZ4, LCZ5, and LCZ6 were the key factors affecting HSR_phy. Our research demonstrates how to quantify heat stress resilience and impact factors of urban physical spaces to provide a basis for developing climate-sensitive urban design strategies.