## 3 Results
### Hydrogeological Risk
The results reveal that the port area, along with the roads and railway, exhibits the highest concentration of illumination, in addition to the densely populated areas. Regarding the hydrogeological risk, the correlation between slope, rainfall, land use, and the percentage of area with high hydrogeological risk was also calculated, as shown Figure 8. The results, shown in the figure, allow us to confirm a strong correlation (as expected) between rainfall and slope with the area at high hydrogeological risk, at 0.83 and 0.80, respectively. \begin{table}
\begin{tabular}{c c} \hline
**Land Use Class** & **High Light Pollution Area Percentage** \\ \hline
11100 Continuous Urban Fabric & 33.3\% \\
11210 Discontinuous Dense Urban Fabric & 16.67\% \\
11220 Discontinuous Medium Density Urban Fabric & 2.13\% \\
11230 Discontinuous Low Density Urban Fabric & 2.08\% \\
11300 Isolated Structures & 1.92\% \\
12100 Industrial, Commercial, Public, Military, and Private Units & 0.88\% \\
12210 Fast Transit Roads and Associated Land & 13.33\% \\
12220 Other Roads and Associated Land & 1.45\% \\
12230 Railways and Associated Land & 5\% \\
12300 Port Areas & 11\% \\
13100 Mineral Extraction and Dump Sites & 1.11\% \\
13400 Low without Current Use & 0.72\% \\
14100 Green Urban Areas & 1.27\% \\
14200 Sports and Leisure Facilities & 0.4\% \\
22000 Permanent Crops & 1.69\% \\
23000 Pastures & 0.75\% \\
31000 Forests & 4.35\% \\
32000 Herbaceous Vegetation Associations & 1.39\% \\
33000 Open Spaces with Little or No Vegetation & 0.53\% \\ \hline \end{tabular}
\end{table} 
Table 2: High light pollution area percentage in land use class. Figure 7: Correlation matrix between light pollution and CO\({}_{2}\). We then proceeded to analyze the risk distribution through boxplots (Figure 9), which allowed us to highlight how some land use classes have a more concentrated distribution with few outliers, while others, such as the class \"12220\", show a greater dispersion with extremely high values. Furthermore, several land use classes have points outside the boxplots, indicating the presence of anomalous values that could represent exceptional events or specific situations. Some categories, such as \"12220\" and \"22000\", show a high variance and higher maximum values, suggesting that these types of land use could be more subject to risk phenomena. Finally, the classes with very compact boxplots and low values indicate that the risk area for those types of land use is generally limited. In summary  
* The most critical classes (12220, 22000, and 31000) have a wide dispersion and extremely high values, indicating a high risk. * The moderate risk classes (12230, 12300, 20000, 30000, 32000, and 33000) have a significant but not extreme variance. * The low-risk classes (11100, 11210, 11220, 11230, 13100, 13400, 14100, and 14200) show a narrower distribution with generally low values. Similarly, for hydrogeological risk, we crossed the areas at high hydrogeological risk with the land use classes; results are shown in Table 3. The analysis revealed that the classes most at risk include Continuous Urban Fabric, Discontinuous Dense Urban Fabric, Discontinuous Medium Density Urban Fabric, Roads and Associated Land, and Port Area (within the city). Also of significance are the areas classified as Pastures and Herbaceous Vegetation Associations, which show notable vulnerability. Figure 8: Correlation matrix between land use, risk area, rainfall, and slope. Figure 9: Distribution of hazard areas by land use class. Light pollution has several adverse effects on public health and significantly impacts urban planning. The excess of artificial light is correlated with an increased risk of metabolic and cardiovascular disorders and also negatively affects the life of the city's fauna. Several techniques can be adopted by public administration to reduce these effects, such as the use of LED lights, smart lighting systems, and the construction of 'dark zones' to preserve local fauna.