During the last decades, a variety of digital tools have been developed to support both the planning and management of cities, as well as the inclusion of civic society. Here, the concept of a Digital Twin – which is rapidly emerging throughout many disciplines due to advances in technology, computational capacities and availability of large amounts of data – plays an important role. In short, a digital twin is a living virtual model, a connected digital representation of a physical system and has been a central concept in the manufacturing industry for the past decades. In this article, we review the terminology of digital twins for cities and identify commonalities and relations to the more established term 3D city models. Our findings indicate an increasing use of the term digital twin in academic literature, both in general and in the context of cities and the built environment. We find that while there is as yet no consensus on the exact definition of what constitutes a digital twin, it is increasingly being used to describe something that is more than a 3D city model (including, e.g. semantic data, real-time sensor data, physical models, and simulations). At the same time, the term has not yet replaced the term 3D city model as the most dominant term in the 3D GIS domain. By looking at grey literature we discuss how digital twins for cities are implemented in practice and present examples of digital twins in a global perspective. Further, we discuss some of the application areas and potential challenges for future development and implementation of digital twins for cities. We conclude that there are significant opportunities for up-scaling digital twins, with the potential to bring benefits to the city and its citizens and clients.

Urban planning needs to face and integrate ecological, social, and economic aspects of city living. So far, attempts to integrate different urban simulation models into one technical platform have focused on quantitative data. The aim of this paper is to present the preparation for an automated method to spatially integrate and visualize interview-based qualitative data on the perception of urban places into a virtual platform. The Gothenburg suburb of Hammarkullen is used as a case study. Two CAQDAS software, NVivo and Atlas.ti, were tested. In both software, locations and urban qualities were coded and clustered. Visualization strategies such as information tree structures, geo-coded quotations, spatial word clouds, linked to 2D maps and 3D environments were developed. Results identify the challenges to overcome and show limitations of the software in terms of creating graphs and relationships as well as automated geocoding of data to maps. The project offers a step towards the integration of qualitative (social) data into digital environments that can be scaled up. By that, it contributes with a new dimension of analysis of urban environments which is necessary for sustainable transformation of cities.

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