This article explores the use of digital twins (DTs) in urban planning, focusing on the development of a DT for the city of Turin, Italy. DTs are virtual replicas of physical environments that integrate real-time data and simulations to enhance decision-making and management processes in urban contexts. They provide a dynamic representation of the city, enabling authorities and planners to visualize urban dynamics, improve understanding of urban ecosystems, energy efficiency, traffic management, and emergency response. DTs support the simulation and modeling of different scenarios in an urban built environment, enabling predictive analysis of transformation decisions and anticipation of future trends and challenges. The paper highlights the assumptions and ongoing progress in the development of a DT for Turin, focusing on applications such as the extraction of built and natural environment features, land use data, road network and pavement quality, and signage, along with continuous model updates over time. The relevance of 3D city models in urban and regional planning is discussed, emphasizing their role in facilitating comprehensive analysis and decision-making in urban contexts. The integration of 3D city models with GIS and real-time data enables dynamic simulation of urban environments, while the potential of augmented reality (AR) and virtual reality (VR) in urban modeling offers immersive experiences that open new frontiers in urban planning and design. The evolution of 3D city models has been significantly shaped by advancements in GIS integration and real-time data assimilation. The fusion of GIS with 3D modeling has enhanced the accuracy and relevance of urban models, while the integration of real-time data into 3D urban models has enabled dynamic simulation of urban environments. Advances in remote sensing data collection techniques, such as LiDAR and photogrammetry, have improved the accuracy and efficiency of capturing urban environments. The integration of 3D city models with GIS platforms and semantic information enables spatial analysis and the visualization of complex urban data. The paper also discusses the transition from 3D city models to urban DTs, highlighting the importance of real-time data and advanced simulation capabilities in urban planning and decision-making. Examples of implemented urban DTs, such as the Zurich Digital Twin and the Helsinki 3D and Kalasatama DT, are presented, illustrating the potential of DT technology in urban planning and management. These examples show how DTs allow for the simulation and analysis of different urban scenarios, facilitating disaster response strategies and infrastructure robustness testing in a virtual environment. The article also discusses the algorithms and software used for the production of 3D city models, emphasizing the importance of data acquisition, processing, and integration in the creation of accurate and detailed 3D models. The integration of IoT and AI significantly enhances DT applications, particularly in the area of urban modeling, enabling them to process vast amounts of data and provide insightful analysis for better decision-making and predictive modeling. The integration of IoT devices leads to increased connectivity and interactivity within the DT, allowing for a more responsive and dynamic model that can adapt to changes in real timeThis article explores the use of digital twins (DTs) in urban planning, focusing on the development of a DT for the city of Turin, Italy. DTs are virtual replicas of physical environments that integrate real-time data and simulations to enhance decision-making and management processes in urban contexts. They provide a dynamic representation of the city, enabling authorities and planners to visualize urban dynamics, improve understanding of urban ecosystems, energy efficiency, traffic management, and emergency response. DTs support the simulation and modeling of different scenarios in an urban built environment, enabling predictive analysis of transformation decisions and anticipation of future trends and challenges. The paper highlights the assumptions and ongoing progress in the development of a DT for Turin, focusing on applications such as the extraction of built and natural environment features, land use data, road network and pavement quality, and signage, along with continuous model updates over time. The relevance of 3D city models in urban and regional planning is discussed, emphasizing their role in facilitating comprehensive analysis and decision-making in urban contexts. The integration of 3D city models with GIS and real-time data enables dynamic simulation of urban environments, while the potential of augmented reality (AR) and virtual reality (VR) in urban modeling offers immersive experiences that open new frontiers in urban planning and design. The evolution of 3D city models has been significantly shaped by advancements in GIS integration and real-time data assimilation. The fusion of GIS with 3D modeling has enhanced the accuracy and relevance of urban models, while the integration of real-time data into 3D urban models has enabled dynamic simulation of urban environments. Advances in remote sensing data collection techniques, such as LiDAR and photogrammetry, have improved the accuracy and efficiency of capturing urban environments. The integration of 3D city models with GIS platforms and semantic information enables spatial analysis and the visualization of complex urban data. The paper also discusses the transition from 3D city models to urban DTs, highlighting the importance of real-time data and advanced simulation capabilities in urban planning and decision-making. Examples of implemented urban DTs, such as the Zurich Digital Twin and the Helsinki 3D and Kalasatama DT, are presented, illustrating the potential of DT technology in urban planning and management. These examples show how DTs allow for the simulation and analysis of different urban scenarios, facilitating disaster response strategies and infrastructure robustness testing in a virtual environment. The article also discusses the algorithms and software used for the production of 3D city models, emphasizing the importance of data acquisition, processing, and integration in the creation of accurate and detailed 3D models. The integration of IoT and AI significantly enhances DT applications, particularly in the area of urban modeling, enabling them to process vast amounts of data and provide insightful analysis for better decision-making and predictive modeling. The integration of IoT devices leads to increased connectivity and interactivity within the DT, allowing for a more responsive and dynamic model that can adapt to changes in real time