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 real-time traffic data, transit data, and travel demand estimated using Twitter data to compare the travel time by car and PT in four cities (São Paulo, Brazil; Stockholm, Sweden; Sydney, Australia; and Amsterdam, the Netherlands) at high spatial and temporal resolutions. We use real-world data to make realistic estimates of travel time by car and by PT and compare their performance by time of day and by travel distance across cities. Our results suggest that using PT takes on average 1.4–2.6 times longer than driving a car. The share of area where travel time favours PT over car use is very small: 0.62% (0.65%), 0.44% (0.48%), 1.10% (1.22%) and 1.16% (1.19%) for the daily average (and during peak hours) for São Paulo, Sydney, Stockholm, and Amsterdam, respectively. The travel time disparity, as quantified by the travel time ratio $$R$$R (PT travel time divided by the car travel time), varies widely during an average weekday, by location and time of day. A systematic comparison between these two modes shows that the average travel time disparity is surprisingly similar across cities: $$R < 1$$R<1 for travel distances less than 3 km, then increases rapidly but quickly stabilises at around 2. This study contributes to providing a more realistic performance evaluation that helps future studies further explore what city characteristics as well as urban and transport policies make public transport more attractive, and to create a more sustainable future for cities.

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.

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. 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.

Current flood risk assessment and decision support tools, the UK Planning Policy Statement 25 and the UK Environment Agency (EA) flood maps,...