AI-Driven Mapping and Economic Assessment of Urban Carbon Wealth and Vegetation Dynamics in Turin Using Sentinel-2 Remote Sensing

Urban green infrastructure plays a critical role in mitigating climate change by sequestering carbon, regulating microclimates, and enhancing urban resilience. This research integrates artificial intelligence (AI), remote sensing, and economic valuation to quantify and evaluate the carbon and ecological value of vegetation across the city of Turin between 2021 and 2023. Using multi-temporal Sentinel-2 imagery processed in Google Earth Engine, vegetation indices (NDVI) were derived and analyzed to capture spatial and seasonal variations in vegetation dynamics. An AI-driven workflow was employed to estimate Above-Ground Biomass (AGB) and corresponding CO₂ sequestration based on established empirical models. The results revealed clear spatiotemporal trends: vegetation density peaked during summer and declined in winter, with interannual variation reflecting the influence of climatic conditions, particularly the drought of 2022. Total annual CO₂ sequestration ranged between 1.50 × 10⁹ and 2.09 × 10⁹ tonnes, corresponding to an economic value of €119–167 billion using the EU Emissions Trading System reference price (€80 t⁻¹ CO₂). High-sequestration zones were concentrated along the Po River corridor, the eastern hillside forests, and major parks such as Parco del Valentino and Parco della Pellerina. By coupling geospatial data with AI-enhanced modeling and economic valuation, this study demonstrates that urban vegetation represents a significant and measurable component of Turin’s natural capital. The developed framework provides a scalable, cost-efficient approach for supporting climate-neutral city strategies and nature-based investment planning across Europe.