The Surface Urban Heat Island Intensity (SUHII) phenomenon is one of the most significant environmental challenges stemming from urbanization, directly impacting quality of life, energy consumption, and urban health. This research aimed to analyze the spatiotemporal patterns of SUHII and identify its influencing factors by examining land surface temperature data derived from MODIS satellite imagery from 2002 to 2023 for the city of Tehran. For analyzing environmental effects, a multivariate OLS regression model with interaction terms was used, and the Mann-Kendall test and VIF were employed to analyze trends and detect multicollinearity among variables, respectively. The results indicated that SUHII intensity exhibited different patterns across seasons, with a significant decreasing trend observed only in winter (Z = –2.09, p = 0.037). The AOD (air pollution) and NDVI (vegetation cover) indices had the greatest impact on urban warming intensity, and the interactive combination AOD × WSA also showed a significant increasing effect. One of the innovations of this study is its focus on long-term seasonal analysis alongside the evaluation of the combined effects of variables—an approach that has been neglected or performed only in aggregate in most previous research. Furthermore, comparing this study with research such as Zhang et al. (2025) and Wang et al. (2020) revealed that the interactive regression statistical method, despite limitations such as the lack of traffic data or detailed building information, can provide greater accuracy in analyzing causal relationships at the urban scale. The findings of this research emphasize that interpreting urban thermal behavior requires attention to the complex interactions between environmental and human variables. In the future, expanding interdisciplinary analyses by integrating human-related data such as traffic, energy consumption, and urban design can provide a more comprehensive understanding of SUHII mechanisms and strategies to mitigate it.