Refocusing City Information Modelling

Issue 46(4) of Built Environment takes a fresh look at the topic of City Information Modelling (CIM) from the perspective of digital planning for sustainable smart cities.

The concept of CIM has quietly emerged, more than a decade ago, as an evolution of Building Information Modelling (BIM) to address larger city-wide challenges, and since then it has been adopted by the software industry and in urban design and planning research and practice circles. It can be found in industry and technology blogs, in presentations and job descriptions, in software demos and videos, and in conference and seminar lists of topics. This tacit acceptance of the term suggests that CIM represents a useful or even necessary concept, providing a focal point to the various actors involved in digital urban design and planning, and in the production of supporting digital technologies. Indeed, from concept to product was a natural step, and several software companies have developed CIM products over the years, for example CityCAD by HolisticCity (, Modelur by AgiliCity (, or CityEngine by ESRI ( to name a few. Also, the major CAD software vendors got involved at some stage but seem to be redirecting attention to new digital twin products, like the iTwin services by Bentley ( Still, unlike the world of buildings, infrastructure and BIM, the city seems to pose too big a challenge to be encapsulated in a single product, and there will most likely be a large variety of CIM applications for different use cases.

Figure 1. Screenshot of CityCAD model

While one might think about digital technologies when hearing the words “City Information Modelling”, in this issue we have tried to focus on what it represents for urban design and planning practice, or better still, its practitioners, in the context of developing sustainable smart cities:

·      How can it support different planning and design processes, standards, actors and stakeholders?

·      How can it leverage the potential of diverse and new data sources to provide insights on the multitude of physical, social and economic layers that make up a city?

·      In what ways will it engage urban design and decision support with artificial intelligence?


To open the proceedings, in “City Information Modelling: a conceptual framework for research and practice in digital urban planning” I have studied everything that has been written about CIM in the academic literature to better understand its characteristics and how its conceptualized by different authors from a range of backgrounds. Eventually coming to define CIM as an ecosystem of interdependent practices and digital technologies for the process of urban design and planning, used interactively and collaboratively by all stakeholders, connected to a data rich and integrated city information database. From this position I develop a conceptual framework of CIM that provides a road map for integrating the various supporting technologies and disciplines of research and practice.

But the journey is complex, and it is important to learn from the related concept of BIM. Ann Kemp offers in “The BIM implementation journey: lessons learned for developing and disseminating City Information Modelling (CIM)” an insightful and extremely knowledgeable view of the development of BIM in the UK and beyond.  This is not simply a historic narrative, but a reflection on the path to digital transformation of the building industry, on the challenges faced, and on the value of taking a more humanistic perspective if we aim for a successful development of CIM. The latest concept emerging in this digitalization journey, currently dominating the headlines, is that of Digital Twins of cities. Bernd Ketzler, Vasilis Naserentin, Fabio Latino, Christopher Zangelidis, Liane Thuvander and Anders Logg carry out in “Digital twins for cities: a state of the art review” a very first review of the field, its relation to the dominant concept of 3D City Models, and explore a range of applications that Digital Twins can offer cities, identifying outstanding challenges for their development and implementation.

As I wrote in a previous post, digital technology is a means to an end, that of developing more sustainable and equitable cities, by people and for people. Coming from the social sciences, Catherine Lido, Phil Mason, Jinhyun Hong, Nadiia Gorash, Obinna C.D. Anejionu and Michael Osborne showcase in “Integrated multimedia city data: exploring learning engagement and greenspace in Glasgow” a holistic, analytic and data-led approach that integrates diverse urban data to give new insights on aspects of social inclusion, to help policy makers and planners make better informed decisions.

Figure 2. Modular development of a Masterplan

To what extent these complex planning and design decisions can be complemented by the artificial intelligence of algorithms, is the subject of the piece by Reinhard Koenig, Martin Bielik, Martin Dennemark, Theresa Fink, Sven Schneider and Norbert Siegmund. In “Levels of automation in urban design through artificial intelligence: a framework to characterize automation approaches”, the authors introduce a classification of urban design automation equivalent to the levels of automation in the car industry, and demonstrate it through the application of different parametric urban design solvers to a series of projects. Such advanced methods and tools, developed in academia, are not necessarily within reach of the average urban design and planning practice. In “Data-Informed Urban Design: An Overview of the Use of Data and Digital Tools in Urban Planning and Design”, Alexander Gösta, André Agi, Jacob Flårback, Jesper Karlsson and Ellen Simonsson investigate the role that data and digital tools play in their everyday practice, through a series of interviews and a workshop. The desire and ambition to deliver designs that are more environmentally and socially sustainable is evident, however it is also clear that there are still many barriers to widespread adoption of such an approach. The people, in this case practitioners, must be considered in terms of useability and ease of access to tools and data, and in terms of education of the coming generations, if digitalization is to deliver its ambitious goals. Todor Stojanovsky, Jenni Partanen, Ivor Samuels, Paul Sanders and Christopher Peters wrap up the issue with “Viewpoint: City Information Modelling (CIM) and digitizing urban design practices”, where they revisit some of the previous points, namely urban design practice, digital tools, automation and AI. From a theoretical perspective, the authors reflect on how to incorporate design theories, urban morphology and environmental perception in CIM tools supported by AI to offer a digitalization process that is rooted in the practices and the established scholarship of urban design.

After this journey in and around CIM, we hope to have pinned down some key concepts and themes, but also opened the debate to new themes that must be put on the agenda of the digitalization of urban design and planning, with the aim of delivering the smart sustainable and equitable cities that we all envision.

Read the issue on CIM, accessible from Ingenta at this link: 


As ever we welcome further Built Environment blogs & tweets on this theme!    


Listing Image/Image 1: Screenshot of CityCAD model (Source:

Image 2: Modular development of a master plan for the Nordwestbahnof area in the city of Vienna. Top: Design solver that includes modules for generating and evaluating the urban designs shown below. The methodology steps are envisioned as: (i) Urban Analyses; (ii) Concept Development; (iii) Design Generation; (iv) Simulation and Analyses; (v) Design Evaluation; (vi) Visualization. (Source: © Richard Koenig. All rights reserved)