Urban Heat Island (UHI) represents a major environmental challenge in rapidly urbanizing regions, influencing thermal comfort, energy consumption, and human health. This study investigates the spatial and seasonal dynamics of Surface Urban Heat Island (SUHI) and Surface Urban Heat Island Intensity (SUHII) in Lisbon, Portugal, by integrating remote sensing data, geospatial analysis, and machine learning techniques. In this framework, Lisbon is established as the primary case study for a detailed spatial and seasonal exploration of urban thermal patterns. Turin is incorporated as a comparative baseline to validate the model's robustness and to evaluate how different climatic and geographical contexts, specifically Mediterranean coastal versus inland continental conditions, influence the drivers of urban heat.