## 2 Materials and Methods
### Implementation of the Proposed Methodology
Its ability to manage large volumes of data and its reliability make it an ideal choice for projects that require a solid foundation for archiving and processing complex data. In addition, PostgreSQL allows for different modes of interaction: data can be loaded and managed via its graphical interface, which is useful for less experienced users, or via the command line using the psql application, offering greater flexibility for more experienced users who want to manage the database with custom queries. The code that manages the visualization and interaction with the urban digital twin is contained within an HTML file. Once loaded into the browser, this file allows access to the application. In addition to the basic structures of web programming, the HTML file includes fundamental components for visualizing and interacting with geospatial data. In particular, one of the main libraries used is Cesium. With Cesium, the system can visualize the geospatial data loaded into the platform and enable navigation through it, making the user experience more engaging and dynamic. Cesium also allows for the visualization of objects and urban structures and provides advanced visualization operations, such as rendering 3D models. In addition to Cesium, the HTML file includes other specialized JavaScript libraries that enable advanced spatial queries. These libraries are essential for managing communication between the database and the frontend, as well as providing additional features like  
Figure 3: Urban digital twin architecture. geometry analysis, elevation management, and temporal data visualization. These features enable the simulation of various urban scenarios over time, such as the evolution of an area or changes in environmental conditions. The integration of these libraries enriches the user experience and ensures effective spatial analysis, which is crucial for monitoring and managing complex geospatial data. The interactivity of the platform is ensured by the two-way communication between the frontend and the database, facilitated via a backend server. In this case, the backend server is managed by a Node.js script, a JavaScript runtime environment that allows the execution of JavaScript code on the server. Node.js is particularly suitable for applications requiring high performance and scalability, such as those handling large amounts of data in real time. The Node.js server acts as an intermediary between the frontend, which interacts with the user, and the backend, which manages the database. This architecture allows data to be loaded at startup through a REST API connection, a methodology that ensures secure and efficient data exchange between the client (browser) and the server. By using a REST API, the system avoids loading the entire dataset into memory at startup, reducing loading times and improving the fluency of the browsing experience. In practice, only the data needed for the initial visualization are loaded, while the remaining data are dynamically retrieved via API requests when the user interacts with the platform. This significantly lightens the local server and optimizes overall performance. Furthermore, communication between the frontend and the backend ensures that all changes made by the user--both in the visualization interface and in spatial analysis operations--are synchronized in real time with the database. This means that any update or change made to the platform, such as adding new data or processing new spatial analyses, is immediately reflected in the database, keeping the data always up to date and consistent. This is particularly useful in contexts where the platform is used by multiple users simultaneously, allowing them to collaborate and share results in real time. As far as satellite data, raster, vectors and drone flight data are concerned, these have been stored in a cloud solution within a geospatial database, based on a scalable and high-performance platform.