Remote SensingBased Quantification of Shanghais Summer Urban Heat-Island Intensity and NDVI

Urban heat island (UHI) elevates land surface temperature (LST) and stresses public health and energy systems. Urban vegetation can lower LST through shading and evapotranspiration, yet practical guidance on how much greening is needed and where to prioritize it remains limited. Focusing on highly urbanized Shanghai, we used Google Earth Engine to integrate Sentinel-2 NDVI with Landsat 8/9 LST and computed district-level summer (JuneAugust 2022) means of NDVI, LST, and surface UHI (SUHI). We assessed vegetationtemperature relationships using Pearson correlation and ordinary least squares. NDVI and LST were strongly and significantly negatively correlated (r 0.73, p < 0.05); districts with higher vegetation cover showed lower LST and weaker UHI. The regression slope indicates that a 0.1 increase in NDVI is associated with ~2.4 C lower district-mean LST. Based on current land-use patterns, we mapped zones with the greatest greening-for-cooling potential to inform zoning-specific strategies. The results provide quantitative evidence that expanding urban green space is an effective pathway to mitigate UHI and enhance climate resilience and public well-being in megacities.