Climate change and the intensification of urban temperatures in recent decades have posed serious challenges to public health, energy consumption, and the overall livability of metropolitan areas. The alteration of thermal comfort patterns is one of the direct consequences of this trend, underscoring the necessity for a more detailed analysis of the relationships between surface thermal variables and human comfort indices. Despite the growing body of research on thermal comfort, studies that simultaneously examine the spatiotemporal dynamics of comfort indices and their relationships with land surface characteristics at the local scale remain limited. In this context, the present study aims to investigate the role of Land Surface Temperature (LST) in the spatial and temporal dynamics of the Universal Thermal Climate Index (UTCI) and to analyze the impact of thermal variations on the intensity of heat stress in the metropolitan area of Tehran.

In this study, seasonal UTCI data were obtained from the global GloUTCI-M dataset with a spatial resolution of 1 km for the period 2001–2021. Daytime Land Surface Temperature (LSTday) data derived from the MODIS sensor were also employed to analyze the statistical relationship between LSTday and UTCI. Temporal trends of the UTCI were analyzed using a linear regression model, while the correlation between the two variables was assessed through the Pearson correlation coefficient. Subsequently, spatial analyses were conducted to identify the spatial patterns of heat stress.

The results indicated that thermal comfort and heat stress conditions in the metropolitan area of Tehran follow distinct seasonal patterns. During winter, most areas are predominantly affected by cold stress, whereas in summer, nearly the entire city is exposed to severe to very severe heat stress. The UTCI values during summer exceeded the 32 °C threshold, indicating a significant risk to public health. The correlation between UTCI and LSTday was positive across all seasons, with the highest correlation observed in winter (r = 0.94) and the lowest in autumn (r = 0.26). Spatial analysis revealed that areas with sparse vegetation, high densities of impervious surfaces, and the presence of metal roofs or asphalted surfaces experience higher LSTday values, resulting in elevated UTCI levels. In contrast, northern areas with more extensive green spaces exhibit lower surface temperatures and, consequently, more favorable thermal comfort conditions during the warmer months. The findings of this study highlight the high intensity of heat stress during the summer and underscore the necessity for the design and implementation of early heat-warning systems, particularly when UTCI values exceed critical thresholds of 26°C and 32°C, which can lead to increased mortality rates and heat-related illnesses.

Overall, the results of this study indicate that Land Surface Temperature (LST) is not only a suitable indicator for characterizing urban thermal conditions but can also serve as a predictive variable in modeling and managing heat-related risks. The findings provide a scientific basis for climate-adaptive urban planning, the design of heat-mitigation policies, and the optimization of energy consumption in Tehran and other cities with similar climatic conditions.