The changes in remoted land surface temperature (LST) triggered by natural and socioeconomic factors in typical Chinese cities

Abstract

Land surface temperature (LST) is influenced by a variety of natural factors and urbanization processes. Using MODIS LST data and the Geodetector model, we compared the spatiotemporal variations of LST and their drivers in super megacities (Beijing, Guangzhou, Shanghai, and Shenzhen), a megacity (Xi'an), large cities (Urumqi and Harbin), and a small and medium-sized city (Lhasa). The LST of super megacities is primarily influenced by socioeconomic factors (11 %–61 %), whereas natural factors significantly impact the LST of large cities and small to medium-sized cities (15 %–58 %). Socioeconomic factors contributed more significantly to daytime LST in Xi’an (68 %). Elevation is a crucial factor influencing the spatial heterogeneity of LST, and the enhanced vegetation index predominantly dictates the spatial variation of LST through its interactions with other factors. The interaction between various factors significantly enhances their contributions to LST. According to the urban heat island ratio index, Lhasa exhibited the highest urban heat stress risk (>0.83) during both day and night, whereas Harbin displayed the lowest (<0.34). Beijing possessed the highest urban heat risk rating among the super megacities. Xi'an's risk level decreased significantly at night. Overall, cities generally exhibited higher levels of heat risk during the day compared to the night.