## 4 Test Results
To evaluate the accuracy of our method, we compared the partitioning in UGCs of the municipality of Pozzuoli obtained using our framework with the one produced by the expert in a supervised mode by directly applying his detailed knowledge of the study area. To produce this partitioning the expert, instead of carrying out this activity starting from the partitioning of the study area in microzones, used local knowledge of the city in his possession, and produced the partitioning of the area of the municipality of Pozzuoli in UGCs on the basis of deductive processes from his experience. He classified each UGC using the labels of the UGA class created previously. We call the UGC constructed by the expert UGC (UGC constructed by the Expert). In Figure 12 is shown the final thematic map of the UGCs created by the expert. In order to evaluate the performance of our method, for each green area class we measured the percentage of the area of UGCs belonging to this UGA class that is covered by UGCEs belonging to the same class. We obtained these results selecting the UGCs and the UGCEs belonging to this class, measuring the area of the intersecting regions between the UGCs and the UGCEs selected and dividing this area by the area of the UGCs selected. In Table 5 are shown the results obtained. Table 5 shows that over 50% of the area of UGCs classified in any class is covered by UCGEs belonging to the same class. Only 52.50% of the area of the UGCs belonging to UGA class 1 are covered by UGCEs belonging to the same class. The remaining 47.50% of this area is largely covered by UCGs belonging to classes 2 and 3, that is, to urban or dense urban areas with a presence of urban greenery (not nothing but minimal); this result can be explained by the fact that, since these areas are not very extensive, the discrepancy is greater compared to the areas of the UGC belonging to this class detected on a more detailed scale by the expert. Figure 11: Thematic map of the reliability of the UGCs. The UGCs with a percentage greater than 80% covered by UGCEs belonging to the same class are the UGCs belonging to the urban area classes 2 and 4. This is because the UGCs belonging to class 2 are mainly well-located industrial areas and those belonging to class 4 mainly refer to a very extensive urbanized region with a high presence of urban greenery, correctly detected with the use of the framework. To complete this comparative analysis, we measured the percentage of the area of UGCEs belonging to each UGA class that is classified in the same class using our framework. We calculated this measure selecting the UGCEs and the UGCs belonging to this class and dividing this area by the area of the UGCEs selected. The results obtained are shown in Table 2.0 \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Urban Green Area Class**} & \multirow{2}{*}{**Area of UGCEs (Hectares)**} & \multicolumn{2}{c}{**Percentage of Area Covered by**} \\  & & **UGCs in the Same Class** \\ \hline
1 & 43.94 & 79.16\% \\
2 & 224.74 & 87.27\% \\
3 & 941.47 & 54.62\% \\
4 & 2615.39 & 85.32\% \\
5 & 482.45 & 90.92\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Percentage of area of UGCEs covered by UGCs of the same urban green area class. Figure 12: UGCE map thematized by UGA class. \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Urban Green Area Class**} & \multirow{2}{*}{**Area of UGCs (Hectares)**} & \multicolumn{2}{c}{**Percentage of Area Covered by**} \\  & & **UGCs in the Same Class** \\ \hline
1 & 66.266 & 52.50\% \\
2 & 212.92 & 92.12\% \\
3 & 655.48 & 64.09\% \\
4 & 2710.65 & 82.32\% \\
5 & 662.56 & 66.21\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Percentage of area of UGCs covered by UGCEs of the same urban green area class.