Summer diurnal LST variability across Local Climate Zones using ECOSTRESS data in Lecce and Milan

The development of GIS-based maps involved calculating the actual morphological parameters of the urban environment and applying fuzzy logic to enhance classification accuracy. This methodology integrates geometric and surface-coverage properties, including the sky view factor (SVF), building surface fraction (BSF), impervious surface fraction (ISF), aspect ratio (AR), and average building height (HM), to classify urban and rural areas into Local Climate Zones (LCZs) following the criteria established by Stewart and Oke. Each 100 × 100 m grid cell was assigned an LCZ category based on the computed morphological parameters, with fuzzy logic employed to account for classification uncertainties. This approach enables the identification of the three most probable LCZs for each grid cell. In the classification process, BSF was utilized to differentiate urban from non-urban areas, applying a threshold value of 1. However, this threshold introduced a potential source of inaccuracy. Furthermore, due to the absence of detailed land cover data for certain LCZ types (e.g., LCZ A–G), these categories were merged into a single class labeled "No Built Area."