The spatial heterogeneity of land surface temperature (LST) within cities is profoundly influenced by the built environment. Although significant progress has been made in the study of the urban thermal environment, there is still a lack of research on how the pattern and structural layout of the built environment affects the thermal environment. In this study, we take the Fifth Ring Road of Beijing as an example, invert the urban LST on the basis of multisource spatial data, characterize the built environment, and use k-means cluster analysis to investigate the main influencing factors of the LST in different functional areas and building patterns within the city, as well as the spatial relationship between the built environment and the urban LST. The results show the following: (1) The urban heat island (UHI) effect occurs to varying degrees over a large part of the study area, and these UHI areas are mainly concentrated in the southwestern part of the city, forming a large contiguous area between the second and fifth ring roads. (2) Class 1 is dominated by transport blocks, Class 3 is dominated by commercial blocks, and Class 5 is dominated by green space blocks, with a clustering index of 0.38. (3) The high-density, high-height class (HH-Class 2) has a greater number of blocks distributed in a ring shape around the periphery of the second ring road. The high-density, low-height class (HL-Class 2) has a relatively small number of blocks but a relatively large area, and the largest blocks are located in the western part of the study area. (4) In the HH and HL building patterns, extreme heat scenarios often occur; from the perspective of functional areas, the probability of extreme heat in the transport block is much higher than that of other functional areas, and except for the HH scenario, the green space functional area plays a very important role in reducing the temperature. This study explores the characteristics of the built environment that influence the urban LST from the perspective of different urban functional zones in cities to provide decision support for quantitative territorial spatial planning, optimization, and management.

Evaluating cooling effects within local climate zones (LCZs) is vital for urban planning, especially in countering urban heat islands and enhancing thermal comfort. While prior research has primarily focused on the influence of land cover type LCZs on land surface temperature in large cities, the role of LCZ characteristics across diverse urban environments in smaller regions remains insufficiently explored. This study investigates the cooling effects of land cover type LCZs within the urban built-up areas at the county level using ECOSTRESS land surface temperature data. We utilized a random forest regression model to assess the impact of LCZ factors—namely, landscape shape index, percentage of landscape, and nearest neighbor distance among six built type LCZs and three land cover type LCZs—on cooling effects. The key findings are as follows: (1) Densely constructed LCZs demonstrated higher land surface temperature due to increased heat retention, with LCZ2 showing the highest mean land surface temperature (37.64 °C), whereas land cover type LCZs, particularly LCZG, recorded significantly lower mean land surface temperature (31.86 °C). (2) Land cover type LCZs were crucial in reducing land surface temperature, with LCZG presenting the most significant cooling effects, ranging from 0.31 to 79.43. LCZA and LCZD displayed comparable cooling effects, with average values of 6.54 and 6.46, respectively. (3) The landscape shape index of the land cover type LCZs themselves contributed most significantly to cooling effects. The percentage of landscape and landscape shape index of LCZ3 and LCZ6 notably influenced cooling effects in LCZA and LCZD, while LCZ5 predominantly affected LCZG. (4) The interactions between key factors and cooling effects were found to be complex and nonlinear. U-shaped effects were observed (e.g., central percentage of landscape affecting LCZA and LCZD, and percentage of landscape in LCZ6 affecting LCZG), alongside inverted U-shaped effects (e.g., landscape shape index in LCZ6 affecting LCZG) and combined effects (e.g., landscape shape index of LCZ3 affecting LCZA). The results emphasize the significance of maintaining contiguous and well-structured land cover type LCZs to optimize cooling effects.