## 1 Introduction
In this context, several authors have shown interest in the implementation of this technology [27; 28; 29]. In particular, the authors in [30] focused on contributing to the conceptualization of the urban digital twin. They mapped the initiatives in terms of applications, inputs, processes, and outputs, identifying the requirements for properly structuring this emerging technology. A comprehensive review of these challenges is presented by [31], which outlines the technical challenges related to implementing urban digital twins, including data quality and standards, interoperability, data integration, complexity, and data ownership. In this field, worthy of citation is the platform Snap4 City. Snap4 City (powered by Fiware) is a relevant platform developed by the University of Turin (also in Italy) for multiple purposes [32]. It is a solution that provides users with access to various services (from traffic to air pollutants) and allows the addition of new services through personalized access after registration. The platform enables the creation of dashboards for a range of use cases, from city management to industry. The technologies used are of high value and are cutting-edge, and the platform is presented as versatile and scalable, capable of adapting to various desired solutions. It also includes personalized videos and tutorials, as well as numerous informative documents on its usage, making the user's experience easier. Regarding the integration of digital twins in urban planning, worthy of note is also the case of the city of Zurich [33]. In detail, the paper analyzed the digital twin of the city of Zurich which is composed of high detailed 3D and GIS Data and is suitable for several urban planning-related applications such as the development of the Municipal Development Plan, for planning the high-rise building, heat reduction, and spread of the urban planning procedure across the population. Another example is provided in [34], where the authors presented the digital twin of the city of Herrenberg, built using a combination of 3D modelling, graph theory applied for street network modelling, wind and urban mobility simulation, and a sensor data network. This model was also validated through a questionnaire distributed to 39 participants. For what concerns the use of digital twin technology for environmental risk management, Ref. [35] proposes an innovative digital twin related to water management, climate change adaption, and disaster risk reduction, introducing real-time dynamic updating into the DK-HIP (hydrological information and prediction) model. The paper also explores the potential for developing HIP digital twins for local rivers and basins. Additionally, Ref. [36] discusses the scientific concept of intelligent disaster prevention and mitigation for infrastructure, based on digital twin technologies. The authors of [37] proposed an innovative framework regarding urban flooding digital twin development; the framework is based on a user-centered design process and includes two main components: a UFDT conceptual model and a generative methodology for its rapid construction and update. Lastly, an in-depth review of the evolution of digital twin smart cities regarding disaster risk management is provided by [38] and by [39]. In recent years, the development of the urban digital twin has seen several improvements, particularly in what concerns risk management. One example is presented in [40] where the authors proposed a digital twin as a solution to address urban heat island challenges, such as higher energy consumption and lower air quality, also offering a case study in the city of Enschede in the Netherlands. Another study [41] developed an urban digital twin with a geospatial dashboard to enable visualization of critical infrastructure vulnerabilities across a range of spatial and temporal scales. In this framework, the main technological limitations are interoperability, multi-scale modeling and simulation, scalability and data management, as well as in their applications in emerging sectors.