Over the last fifty years, research into street networks has gained prominence with a rapidly growing number of studies across disparate disciplines. These studies investigate a wide range of phenomena using a wealth of data and diverse analytical techniques. Starting within the fields of transport or infrastructure engineering, street networks have commonly been treated as sets of more or less homogeneous linear elements, connecting locations and intersecting at junctions. This view is commonly represented as a graph, which provides a common and rigorous formalisation accessible across disciplines and is particularly well-suited for problems such as flow optimisation and routing. Street networks are, however, complex objects of investigation and the way we model and then represent them as graphs has fundamental effects on the outcomes of a study. Many approaches to modelling street networks have been proposed, each lending itself to different analyses and supporting insights into diverse aspects of the urban system. Yet, this plurality and the relation between different models remains relatively obscure and unexplored. The motivations for adopting a given model of the network are also not always clear and often seem to follow disciplinary traditions. This paper provides an overview of key street network models and the prima facie merits of pertinent alternative approaches. It suggests greater attention to consistent use of terms and concepts, of graph representations and practical applications, and concludes with suggestions for possible ways forward.

cities worldwide are pursuing policies to reduce car use and prioritise public transit (pt) as a means to tackle congestion, air pollution, and greenhouse gas emissions. the increase of pt ridership is constrained by many aspects; among them, travel time and the built environment are considered the most critical factors in the choice of travel mode. We propose a data fusion framework including realtime traffic data, transit data, and travel demand estimated using Twitter data to compare the travel time by car and pt in four cities (

Typologies have always played an important role in urban planning and design practice and formal studies have been central to the field of urban morphology. These studies have predominantly been of a historical-qualitative nature and do not support quantitative comparisons between urban areas and between different cities, nor offer the precise and comprehensive descriptions needed by those engaged in urban planning and design practice. To describe contemporary urban forms, which are more diffuse and often elude previous historic typologies, systematic quantitative methods can be useful but, until recently, these have played a limited role in typo-morphological studies. This paper contributes to recent developments in this field by integrating multi-variable geometric descriptions with inter-scalar relational descriptions of urban form. It presents typologies for three key elements of urban form (streets, plots and buildings) in five European cities, produced using statistical clustering methods. In a first instance, the resulting typologies contribute to a better understanding of the characteristics of streets, plots and buildings. In particular, the results offer insight into patterns between the types (i.e., which types are found in combination and which not) and provide a new large scale comparative analysis across five European cities. To conclude, we establish a link between quantitative analysis and theory, by testing two well-known theoretical propositions in urban morphology: the concept of the burgage cycle and the theory of natural movement.

With increased interest in the use of network analysis to study the urban and regional environment, it is important to understand the sensitivity of centrality analysis results to the so-called “edge effect”. Most street network models have artificial boundaries, and there are principles that can be applied to minimise or eliminate the effect of the boundary condition. However, the extent of this impact has not been systematically studied and remains little understood. In this article we present an empirical study on the impact of different network model boundaries on the results of closeness and betweenness centrality analysis of street networks. The results demonstrate that the centrality measures are affected differently by the edge effect, and that the same centrality measure is affected differently depending on the type of network distance used. These results highlight the importance, in any study of street networks, of defining the network's boundary in a way that is relevant to the research question, and of selecting appropriate analysis parameters and statistics.

Current flood risk assessment and decision support tools, the UK Planning Policy Statement 25 and the UK Environment Agency (EA) flood maps, focus on the areas directly affected by flooding; however they do not address the indirect consequences of flooding on the existing street network. Research has been done in transport network reliability and resilience to disasters but little application exists to the floods scenario. In this paper we introduce a methodology developed at Space Syntax Limited to analyse and visualise the wider impact of flooding on the urban street network, measuring its performance in order to respond to the situation more effectively. Starting from a hypothetical scenario of floods in London affecting the areas within the highest risk flood Zone 3 as defined by the EA, we use a spatial model of London up to the M25 circular motorway and run network analysis algorithms before and after the flooding. Using a GIS we quantify the extent to which flooding affects the global structure of the city and the spatial accessibility of town centres. The analysis also provides indicators of traffic level distributions to evaluate the performance of the strategic transport network revealing a dependency on the M25 in the flooded scenario for longer trips across London, suggesting congestion levels beyond its capacity. With this work we demonstrate that space syntax network analysis provides objective indicators to demonstrate the indirect impacts of flooding on urban street networks which can be used by relevant authorities to support a future vision and their investment decisions concerning preventative strategies, disaster management and repair.

This article proposes urban network models as instruments to measure urban form, structure, and function indicators for the assessment of the sustainable mobility of urban areas, thanks to their capacity to describe the detail of a local environment in the context of a wider city‐region. Drawing from the features of existing street network models that offer disaggregate, scalable, and relational analysis of the spatial configuration of urban areas, it presents a multimodal urban network (MMUN) model that describes an urban environment using three systems—private transport (i.e., car, bicycle, and pedestrian), public transport (i.e., rail, tram, metro, and bus), and land use. This model offers a unifying framework that allows the use of a range of analysis metrics and conceptions of distance (i.e., physical, topological, and cognitive), and aims to be simple and applicable in practice. An implementation of the MMUN is created for the Randstad city‐region in the Netherlands. This is analyzed with network centrality measures in a series of experiments, testing its performance against empirical data. The experiments yield conclusions regarding the use of different distance parameters, the choice of network centrality metrics, and the relevant combinations of multimodal layers to describe the structure and configuration of a city‐region.

The present policy objective of sustainable urban development has created the need for methods of ex ante evaluation of local area development projects that assess the contribution of alternative solutions to the general sustainability goals. For this reason, we have seen the evolution of building energy assessment methods into sustainable neighbourhood assessment methods that are more integrative and contextual to accommodate the complexities of the urban scale. This article identifies and reviews a selection of sustainable urban development evaluation tools that are applicable to the early stages of urban design projects, to provide a clearer picture of the state of play to those needing to use such tools and those wanting to develop new ones. The review follows an analytical framework covering the format, structure, content and output of the tools, based on the recommendations of planning evaluation theory and the requirements of urban design practice. Since no single tool stands out from the review, the choice is not simple and there is scope both to further improve existing tools and develop new ones. The paper concludes proposing a strategy for the development of robust and compatible sustainable urban development evaluation methods based on four goals: collaboration, compatibility, customisation and combination.

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