The urban heat island ($UHI$) refers to the land surface temperature (LST) difference between urban areas and their undeveloped or underdeveloped surroundings. It is a measure of the thermal influence of the urban built-up area expansion ($UBAE$), a topic that has been extensively studied. However, the impact of $UBAE$ on the LST differences between urban areas and rural areas ($UH{I}_{U-R}$) and between urban areas and emerging urban areas ($UH{I}_{U-S}$) in different seasons has seldom been investigated. Here, the $UH{I}_{U-S}$ and $UH{I}_{U-R}$ in 34 major metropolitan regions across China, and their spatiotemporal variations based on long-term space-borne observations during the period 2001–2020 were analyzed. The $UBAE$ quantified by the difference in landscape metrics of built-up areas between 2020 and 2000 and their impact on $UHI$ was further analyzed. The $UBAE$ is impacted by the level of economic development and topography. The $UBAE$ of cities located in more developed regions was more significant than that in less developed regions. Coastal cities experienced the most obvious $UBAE$, followed by plain and hilly cities. The $UBAE$ in mountainous regions was the weakest. On an annual basis, $UH{I}_{U-R}$ was larger than $UH{I}_{U-S}$, decreasing more slowly with $UBAE$ than $UH{I}_{U-S}$. In different seasons, the $UH{I}_{U-S}$ and $UH{I}_{U-R}$ were larger, more clearly varying temporally with $UBAE$ in summer than in winter, and their temporal variations were significantly correlated with $UBAE$ in summer but not in winter. The seasonal difference in $UH{I}_{U-R}$ was larger than that of $UH{I}_{U-S}$. Both the $UH{I}_{U-S}$ and $UH{I}_{U-R}$ in coastal cities were the lowest in summer, decreasing the fastest with $UBAE$, while those in mountain cities decreased the slowest. The change in the density of built-up lands was the primary driver affecting the temporal variations in $UH{I}_{U-S}$ and $UH{I}_{U-R}$ during $UBAE$, followed by changes in proportion and shape, while the impact of the speed of expansion was the smallest, all of which were more obvious in summer than in winter. The decreased density of built-up lands can reduce $UHI$. These findings provide a new perspective for a deeper understanding of the effect of urban expansion on LST in different seasons.

Land surface temperature (LST) is a key indicator of the urban heat island effect and is affected by multiple factors. However, existing research mainly focuses on the contributions of urban landscape and meteorology, and the impact of changes in atmospheric environment has not been fully considered. Based on multisource data and a random forest model, this study quantified the independent and interactive effects of aerosols, meteorological conditions, and urban features on LST in Beijing. The results revealed that the effects of the meteorological factors and aerosol optical depth (AOD) on LST were significantly greater than those of the urban landscape index. The response of LST to multiple factors is nonlinear, and the interactions of precipitation with wind speed and vegetation have the strongest cooling effects on LST. The aerosol impact shifts seasonally, with its direct radiative effect dominating in spring and inducing a cooling of up to about 2.0 °C. Notably, the land use type plays a background role in determining the LST, and the average LST decreases by approximately 1.5 °C for every 50% increase in tree coverage. As the building height increases by 10%, the summer LST increases by approximately 2 °C. In addition, the interactions of precipitation with wind speed and vegetation were identified as having the strongest cooling effects on LST. By elucidating the nonlinear interactions among aerosol, meteorological, and urban features, this work moves beyond isolated factor analysis and offers mechanism cognition for urban planning strategies.