Finding a method to evaluate people’s emotional responses to urban spaces in a valid and objective way is fundamentally important for urban design practices and related policy making. Analysis of the essential qualities of urban space could be made both more effective and more accurate using innovative information techniques that have become available in the era of big data. This study introduces an integrated method based on geographical information systems (GIS) and an emotion-tracking technique to quantify the relationship between people’s emotional responses and urban space. This method can evaluate the degree to which people’s emotional responses are influenced by multiple urban characteristics such as building shapes and textures, isovist parameters, visual entropy, and visual fractals. The results indicate that urban spaces may influence people’s emotional responses through both spatial sequence arrangements and shifting scenario sequences. Emotional data were collected with body sensors and GPS devices. Spatial clustering was detected to target effective sampling locations; then, isovists were generated to extract building textures. Logistic regression and a receiver operating characteristic analysis were used to determine the key isovist parameters and the probabilities that they influenced people’s emotion. Finally, based on the results, we make some suggestions for design professionals in the field of urban space optimization.

Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal methods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility. For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages.

Virtual reality is the logical step that started way back in time with the appearance of the very first architectural drawing. This has been a long history of development: architectural drawings in Europe, which date back to the tenth century, were the first kind of abstraction that appeared “virtually real” to potential clients and builders—real enough to base decisions on. With the discovery of perspective techniques, drawings became more refined and developed into a form of art with numerous branches, ranging from technical drawings to presentation drawings. Wooden models appeared even before the Renaissance and were supplemented in the nineteenth century with cardboard models. Each new invention helped to improve the understanding of projects and architecture by reducing abstraction, while increasing the complexity of the representation (Schmitt, 1993). Toward the end of the twentieth century, the majority of architectural projects were and are never realized. Prominent projects, such as the new Berli...

It is our goal to make today’s and future cities smart, sustainable and resilient. In order to achieve this, it is fundamental to understand how each city works, to formalize the knowledge gained and to apply it to a city model as the base for simulations that can generate future scenarios with a high level of probability. The nature of this model, which must cover design, qualitative and quantitative aspects, has changed over time. In this study, we focus on the role of the spatial dimension and of geometry in a city model. Emerging from being a dominating generative force in ancient cities, spatial modeling has developed into an underlying description language for present and future cities to define functions and properties of the city in space and time. The example of the stocks and flows model applied to the city depicts where and how spatial modeling influences the design, construction and performance of the future Smart City.