Urban spaces consist of a complex collection of buildings, parcels, blocks and neighbourhoods interconnected by streets. Accurately modelling both the appearance and the behaviour of dense urban spaces is a significant challenge. The recent surge in urban data and its availability via the Internet has fomented a significant amount of research in computer graphics and in a number of applications in urban planning, emergency management and visualization. In this paper, we seek to provide an overview of methods spanning computer graphics and related fields involved in this goal. Our paper reports the most prominent methods in urban modelling and rendering, urban visualization and urban simulation models. A reader will be well versed in the key problems and current solution methods.

Final designNon-optimized sun exposure and interior light Initial residential place types Non-optimized distance to closest park Development site a b c d f e Figure 1: Example Urban Design Process. The user interactively controls a 3D urban model by altering the parameters of an underlying procedural model (forward modeling) or by changing the values of arbitrary target indicator functions (inverse modeling). a) Starting with a development site, b) the user selects an initial urban layout (using templates or "place types"). The layout now has parcel egress but has c) initial undesired values of building sun-exposure and natural interior light, and d) unwanted average distance from buildings to closest parks.The model alterations needed to obtain user-specified local or global values for these indicator values are computed "inversely" resulting in a final design, which is e) seen up close or f) from a distance. In contrast, accomplishing such an output with traditional forward modeling would require either specifically writing a procedural model with the desired parameters or very careful parameter tuning by an expert to obtain the intended results. AbstractWe propose a framework that enables adding intuitive high level control to an existing urban procedural model. In particular, we provide a mechanism to interactively edit urban models, a task which is important to stakeholders in gaming, urban planning, mapping, and navigation services. Procedural modeling allows a quick creation of large complex 3D models, but controlling the output is a wellknown open problem. Thus, while forward procedural modeling has thrived, in this paper we add to the arsenal an inverse modeling tool. Users, unaware of the rules of the underlying urban procedural model, can alternatively specify arbitrary target indicators to control the modeling process. The system itself will discover how to alter the parameters of the urban procedural model so as to produce the desired 3D output. We label this process inverse design.

The main contribution of our work is in closing the loop between behavioral and geometrical modeling of cities. Editing of urban design variables is performed intuitively and visually using a graphical user interface. Any design variable can be constrained or changed. The design process uses an iterative dynamical system for reaching equilibrium: a state where the demands of behavioral modeling match those of geometrical modeling. 3D models are generated in a few seconds and conform to plausible urban behavior and urban geometry. Our framework includes an interactive agent-based behavioral modeling system as well as adaptive geometry generation algorithms. We demonstrate interactive and incremental design and editing for synthetic urban spaces spanning over 200 square kilometers.

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