Rapid urbanization has intensified environmental challenges such as the urban heat island effect and rising land surface temperatures (LSTs), especially in megacities like Tehran. As impervious surfaces replace natural landscapes, the surface energy balance is disrupted, leading to elevated urban temperatures. These shifts significantly affect public health, urban sustainability, and residents’ quality of life, particularly where human activities and mobility patterns are concentrated. This chapter explores the spatial relationship between private automobile travel frequency and LST variations across Tehran’s 22 districts using a crowdsensing-based approach. By combining satellite-based remote sensing and crowdsensed mobility data, the study offers a multidimensional analysis of urban thermal dynamics. Land surface temperature data were extracted from thermal infrared imagery acquired via Landsat between 2001 and 2024. These long-term datasets enabled high-resolution monitoring of temperature trends across time and space. In parallel, private car mobility data were obtained through Tehran Municipality’s traffic monitoring systems, including license plate recognition and vehicle flow analysis. The findings reveal that in 12 districts, car trip frequencies and LST variations exhibit a positive correlation, while in 8 districts, this relationship is negative. Additionally, two districts showed no significant correlation between these variables. The results underscore the utility of integrating remote sensing with crowdsensed data for evaluating human–environment interactions in urban areas. Moreover, this approach highlights the value of incorporating mobility trends into climate-sensitive urban planning and urban heat island mitigation strategies.