Environment and Planning B: Urban Analytics and City Science

In light of the urgent threats presented by climate change and rapid urbanisation, interest in ‘smart city systems’ is mounting. In contrast to scholarship that poses ‘smartness’ as something that needs to be added to cities, recent developments in spatial morphology research pursue a view of the built fabric of cities as an extension of the cognitive human apparatus, as well as a material formulation of social, cultural and economic relations and processes. The built fabric of cities needs to be understood as a highly intelligent artefact in itself, rather than simple, dead matter. The current focus on high-tech systems risks concealing the fact that the machine is already there. In contrast to the technological ‘implements’ of smart city systems, this article looks at cities as ‘facilities’ – that is, as technologies that slow down, store and maintain energy as a resource for a variety of purposes. The article builds on space syntax research in order to give precision to the understanding of the affordances the cities offer their various processes and the ways in which cities operate as information storage and retrieval devices for individuals and for society. The city must be considered, we argue, in terms of a range of tangled, interdependent systems, reaching from individual buildings to the whole city, an understanding anchored in notions of ‘diversity’ and ‘density’ (recently gathered under the concept of ‘spatial capital’) and in research addressing how the distribution of space and artefacts serve as means of knowledge communication (specifically, in complex buildings such as libraries and department stores). In conclusion, we argue that existing discussions on ‘smart city systems’ would benefit acknowledgement of the role of cities as facilities.

This article describes the development of a new three-dimensional model of the British building stock, called ‘3DStock’. The model differs from other 3D urban and stock models, in that it represents explicitly and in detail the spatial relationships between ‘premises’ and ‘buildings’. It also represents the pattern of activities on different floors within buildings. The geometrical/geographical structure of the model is assembled automatically from two existing national data sets. Additional data from other sources including figures for electricity and gas consumption are then attached. Some sample results are given for energy use intensities. The first purpose of the model is in the analysis of energy use in the building stock. With actual energy data for very large numbers of premises, it is possible to take a completely new type of statistical approach, in which consumption can be related to a range of characteristics including activity, built form, construction and materials. Models have been built to date of the London Borough of Camden and the cities of Leicester, Tamworth and Swindon. Work is in progress to extend the modelling to other parts of Britain. Because of the coverage of the data, this will be limited however to England and Wales.

The street network is an important aspect of cities and contains crucial information about their organization and evolution. Characterizing and comparing various street networks could then be helpful for a better understanding of the mechanisms governing the formation and evolution of these systems. Their characterization is however not easy: there are no simple tools to classify planar networks and most of the measures developed for complex networks are not useful when space is relevant. Here, we describe recent efforts in this direction and new methods adapted to spatial networks. We will first discuss measures based on the structure of shortest paths, among which the betweenness centrality. In particular for time-evolving road networks, we will show that the spatial distribution of the betweenness centrality is able to reveal the impact of important structural transformations. Shortest paths are however not the only relevant ones. In particular, they can be very different from those with the smallest number of turns—the simplest paths. The statistical comparison of the lengths of the shortest and simplest paths provides a nontrivial and nonlocal information about the spatial organization of planar graphs. We define the simplicity index as the average ratio of these lengths and the simplicity profile characterizes the simplicity at different scales. Measuring these quantities on artificial (roads, highways, railways) and natural networks (leaves, insect wings) show that there are fundamental differences—probably related to their different function—in the organization of urban and biological systems: there is a clear hierarchy of the lengths of straight lines in biological cases, but they are randomly distributed in urban systems. The paths are however not enough to fully characterize the spatial pattern of planar networks such as streets and roads. Another promising direction is to analyze the statistics of blocks of the planar network. More precisely, we can use the conditional probability distribution of the shape factor of blocks with a given area, and define what could constitute the fingerprint of a city. These fingerprints can then serve as a basis for a classification of cities based on their street patterns. This method applied on more than 130 cities in the world leads to four broad families of cities characterized by different abundances of blocks of a certain area and shape. This classification will be helpful for identifying dominant mechanisms governing the formation and evolution of street patterns.

We propose a GIS-based method to enable the understanding of how global street-network properties emerge from the temporal accumulation of individual street-network increments. The method entails the adoption of quantitative descriptions of individual street-patterns and of classification algorithms, in order to obtain numerically defined typomorphologies, which may then be statistically associated with the numerical outputs of street-network analysis. We apply the method to the case of Oporto Metropolitan Area, whose development we observed over 60 years. We isolate each increment of development entailing the creation of new streets (4208 objects), we quantify the morphology of their street-layouts, and we classify them into typomorphologies with clustering techniques. Through the investigation of the temporal and spatial frequencies of those typomorphologies, we assess their impacts on the street-networks of a set of selected civil-parishes of the metropolitan region, demonstrating that different typomorphological frequencies result in also different global street-network properties. We conclude by summarising the advantages of the method to generic urban morphological research and by suggesting that it may also contribute to inform bottom-up metropolitan spatial planning.

The diurnal movements of pedestrians in the built environment are sometimes typified as a ‘street ballet’, where each actor or dancer has their own set role within a larger complex. Every individual in the ballet may have many influences on their behaviour including the physical layout of the environment, cognitive strategies to navigate it, experiential or affective preferences as well as social, economic and political factors, but ultimately each one seems to obey apparently choreographed actions. The aim of this article is to understand whether or not there is in fact an underlying choreography to the ballet, in that certain steps or moves are more likely than others, such that a ‘dance’ through daily life is constructed. To do so, simple automata that use active perception to inhabit the world are evolved against different tasks within the environment, representing different sets of moves that may be taken. It is shown that any evolved automaton appears to embody a mathematical person–space relationship that joins visual affordance with motor action: the convergence of a simple Markov model of visual movement. From the Markov model, a general model of embodied action in the environment is proposed, whereby memory of the dance is ingrained over evolutionary history, such that it forms building blocks for non-discursive action within the built environment and comprises a possible common phenomenological framework.

In this study, we empirically model the interactions between 2D and 3D geospatial information and both daytime and nighttime urban heat islands, and estimate the relative importance of various urban heat islands drivers. While previous studies have explored the relationship between the urban heat islands and 2D urban features, the interactions with 3D urban features and neighboring surface characteristics have not been adequately explored. This paper specifies the impacts of these urban features on the urban heat islands intensity during daytime and nighttime, which tend to be quite different. The empirical evidence from this study suggests that while vegetation is the dominant factor for urban heat islands intensity during daytime, the urban canyon has stronger impacts on the urban heat islands than vegetation at night. In addition, adjacent surfaces are more likely to influence nighttime surface temperatures. These results could be used to develop urban design solutions for mitigating the urban heat islands.

The present study aims at exploring whether aspects of urban form (compactness ratio and elongation ratio) are associated with urban smog (particulate matter) in China. Quantitative indicators relating to urban form and urban smog were selected and quantified for 30 Chinese cities, for the reference years 2000, 2007, and 2010, by using a combination of compiled statistical data, remote sensing, and geographical information system data. Panel data analysis was used to evaluate the degree of association between measures of urban form and urban smog, while controlling for urban population, built-up area green coverage rate, power consumption, SO₂ emissions, gross value of industrial output, gross industrial output, and buses per capita. The results indicate that urban compactness and urban elongation were positively correlated to urban particulate matter. It is therefore recommended to consider the implication of urban form on smog as part of urban planning and as part of ongoing strategies to mitigate the deleterious consequences of air pollution.

This article tests the extent to which a measure of walkable access is a good proxy for the quality of the walking environment. Based on existing findings on inequalities of walkability, we ask whether this relation varies between neighborhoods with low and high incomes. Walk Score is used to measure walkable access while the State of Place Index is applied to synthesize the qualitative urban form dimensions collected as part of the Irvine Minnesota Inventory. Simple bivariate correlations and difference-in-means tests assess the relationship and difference in average scores between the two. We draw on an existing sample of 115 walkable neighborhoods in the Washington, DC metro area that Mariela Alfonzo and colleagues had collected for previous research and that we augmented to include additional low-income neighborhoods. Our results reveal a strong and positive overall association between walkable access (Walk Score) and walkability (State of Place). However, this association masks problems with the quality of the walking environment that are significantly larger in low-income neighborhoods (even those with very good walkable access), especially regarding connectivity, personal safety, and the presence of litter and graffiti. As a proxy for walkability, Walk Score’s walkable access measure is, therefore, not equally strong across all neighborhoods but declines with income. In this sense, Walker’s Paradise is more walkable in higher than low-income neighborhoods.

France has developed a high quality motorway system that has been rapidly rationalised and matured in the late 20th century yet has been founded on ancient, Roman infrastructures. The development of the motorway system is thus an iterative method associated with hierarchical ‘top-down’ processes taking into consideration factors such as population density, network demand, location of natural resources, civil engineering challenges and population growth. At the opposite extreme to this approach is the development of transport networks within simple biological systems which are typically decentralised, dynamic and emerge from simple, local and ‘bottom-up’ interactions. We examine the notion, and to what extent, that the structure of a complex motorway network could be predicted by the transport network of the single-celled slime mould Physarum polycephalum. This comparison is explored through its ability to ‘deduce’ the French motorway network in a series of analogue and digital experiments. We compare Physarum network and motorway network topology in relation to proximity graphs and assess the trade-off between connectivity and minimal network length with a bottom-up model of a virtual plasmodium. We demonstrate that despite the apparent complexity of the challenge, Physarum can successfully apply its embodied intelligence to rationalise the motorway topology. We also demonstrate that such calculations prove challenging in the face of significant obstacles such as, mountainous terrain and may account for the missing route between Nice, Grenoble, Avignon and Lyon. Finally, we discuss the topological findings with respect to circle and spoke city planning infrastructures and certain species of web-building spiders.