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In this research open data from sources such as NASA's Landsat-8 and 9 and the Copernicus Programme's Sentinel-1 and 2 were used. These data, combined with open street map databases and information from Italy's Real Estate Market Observatory (OMI), were analyzed using QGIS. Landsat-8 and 9 images were used to calculate daytime summer Land Surface Temperature (LST), while Sentinel-2 images provided detailed layers of urban features such as tree cover and grasslands. The impervious surfaces were determined by processing the land consumption map by ISPRA/SNPA. The study divided municipal territories into different zones using the OMI methodology, classifying urban areas from central to peripheral. It also applied ISPRA’s urbanization level based on artificial surface density thresholds. Both approaches revealed evident SUHI effects with the highest values observed in cities such as Genoa, Trieste, and Turin with mean surface temperature differences between central and peripheral areas ranging from 2 to 6 °C. The highest temperature differences were observed using the urbanization level approach. The results will be made available through a WebGIS tool to help Public Administrations (PAs) plan interventions to mitigate SUHI effects. |
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