## 3 Results
### Hydrogeological Risk  
The first results obtained have marked a significant advancement in the field of advanced digital modeling. The three-dimensional modeling provided a precise representation of the morphological characteristics of the territory, enabling the integration of  
Figure 5: Preview of the urban digital twin of Reggio Calabria: 3D representation of light pollution expressed in radiative flux. accurate geospatial data. This integration allowed the identification of areas at risk based on land use, which is crucial for assessing and mitigating potential hazards. The model was specifically designed to simulate hydrogeological risk scenarios, allowing for the evaluation of potential impacts on infrastructures, buildings, and the population. In this case, it was possible to identify the areas that are most susceptible to flooding within the city center, which is especially valuable for urban planning and emergency response. By extending this study to incorporate various potential scenarios and configurations, the model can offer crucial insights into flood risk and related landslide risks. Such detailed assessments will support decision making in urban resilience and sustainability efforts, helping to develop proactive strategies for managing and mitigating environmental risks. Figure 6 shows in red the 3D representation of the urban center subjected to hydrogeological risk and in blue the basin area with the calculation of the stream segments of flow directions. Overall, the proposed urban digital twin system architecture offers a multi-layered and flexible framework that supports the integration of real-time data from both on-site and satellite sensors. These sensors feed data into the system using the MQTT communication protocol, a lightweight and efficient solution for transmitting real-time data with low bandwidth consumption, making it ideal for IoT applications where frequent updates are required. Once the data are transmitted, they are processed and stored in relational databases, which simplifies data integration from various sources, ensuring that the system remains adaptable and scalable. This architecture allows the model to be easily extended to include new devices and additional data sources as they become available, ensuring its long-term relevance and versatility. The simulation and experimental setup were designed to evaluate the accuracy and effectiveness of the urban digital twin in modeling flood risk and light pollution. For the flood risk simulation, the HEC-RAS (v. 6.6) 2D hydraulic model was employed to simulate water flow dynamics based on the Saint-Venant equations. Input data included high-resolution Digital Elevation Models (DEMs), land cover classification, river discharge data, and precipitation records. Boundary conditions were defined using historical flood events, and sensitivity analysis was conducted to optimize model parameters such as the Manning's roughness coefficient. For the light pollution analysis, satellite data from VIIRS-DNB were integrated with ground-based light intensity measurements. Regarding light pollution, the proposed methodology allowed the evaluation of the correlation between light pollution and the concentration of carbon dioxide in the study  
Figure 6: Preview of the urban digital twin of Reggio Calabria: 3D representation of hydrogeological risk. area. Correlation is shown in Figure 7. The analysis revealed a correlation of over 0.5 between these two variables, indicating a sufficient positive correlation. This suggests that as one variable increases, the other does as well. Regarding the areas most affected by the phenomenon of light pollution, it was possible to estimate the results reported in the following Table 2:  
The light pollution data detected by satellites and sensors were cross-referenced and integrated with land use data to quantitatively determine the areas that are most at risk of higher radiance during the night.