## 5 Results and Discussion  
### UHIs Detected  
The clusters obtained from the FCM were classified based on the LST and NDVI values and divided into nine classes; the first class represents the clusters that have a high degree of LST and a low level of NDVI; on the contrary, class 9 groups the clusters that record the lowest LST value and the highest degree of NDVI. The classification result is shown in Figure 7.  
Following the classification of the FCM results and based on the hot and cold thresholds shown in Figure 6, the clusters that constitute cold and hot spots were identified. The polygons belonging to the clusters that exceed the cold threshold (9, 1, and 8, in turn reclassified as 9, 8, and 7) were grouped to determine the cold spots of the study area; similarly, the polygons belonging to the clusters that are below the hot threshold (3, 4, and 6, in turn reclassified as 3, 2, and 1) were grouped to determine the hotspots of the study area. The hot and cold spot detection result is shown in Figure 8.  
The thematic map delineates a pronounced prevalence and spatial distribution of cold spots in the northwestern and western regions of the study area. This pattern is primarily attributable to the substantial presence of green spaces in these zones, where vegetation plays a critical role in modulating ambient temperatures and inhibiting the formation of UHIs. The inverse is evident in the prominent hotspot extending from the central to the eastern periphery of the study area. This zone is typified by a dense urban fabric, extensive industrial complexes, and a notable scarcity of vegetation, all of which contribute to the intensification of heat. Figure 7: Thematic map of the FCM’s output classification. The northern region constitutes an anomaly in this context, as it, despite being characterized by an abundance of medium-sized green spaces, represents a significant hotspot. This localized thermal anomaly may be attributed to the specific nature of the greenery present. Unlike the western sector, which predominantly features shrubland and woodland vegetation types, the northern area is primarily dominated by urban green spaces, such as decorative flowerbeds, which lack the substantial canopy cover provided by medium to large trees. Consequently, these urban greenspaces may offer insufficient thermal mitigation compared to more substantial, natural vegetation types. Finally, a reliability analysis was performed to measure the average value of the maximum membership degree of each hotspot; three classes were created based on the value of the membership degree: _Low, Medium_, and _High_. The _Low_ class groups hotspots with a degree lower than 0.50; the Medium class contains hotspots with a degree equal to or greater than 0.50 and less than 0.75; and the _High_ class includes hotspots with a degree equal to or greater than 0.75. The spatial distribution of the reliability classes is shown in the thematic map in Figure 9.  
The areas to the north and east of the study area exhibit the most extensive UHIs. As previously mentioned, the causes are to be found in the typology of the urban fabric that characterizes these areas, predominantly devoid of green spaces but rich in impermeable surfaces. Evaluating the reliability of each hotspot, it is possible to note that the vast majority of the UHIs identified have a _High_ value. Table 1 shows the percentages of UHI areas divided into reliability classes calculated with respect to their overall surface. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Reliability Class** & **Area [km\({}^{2}\)]** & **Percentage** \\ \hline High & 43.87 & 94.26\% \\ Medium & 2.62 & 5.63\% \\ Low & 0.05 & 0.11\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Percentage distribution of the average reliability classes of UHIs. Figure 8: Hotspot and Coldspot detection. The sum of the UHI areas amounts to 46.54 km\({}^{2}\) and represents 39.92% of the entire study area, which measures 118.38 km\({}^{2}\). About 95% of these UHIs have a reliability of High, which exceeds 0.75.