This thesis investigates the Urban Heat Island (UHI) effect in Turin, Italy, through an integrative approach that combines geospatial analysis, remote sensing, and 3D modeling to identify UHI-prone areas and propose mitigation strategies. The research employs advanced remote sensing techniques using Google Earth Engine to collect and analyze satellite imagery and temperature data, identifying regions susceptible to higher temperatures due to dense infrastructure and limited vegetation. Detailed 3D modeling using the Dragonfly plugin in Rhino software enables a comprehensive simulation of UHI dynamics under various climate scenarios. Future weather data projections, generated using the CCWorldWeatherGen tool, provide insights into the potential intensification of UHI effects by 2050 and 2080.