Street Network Studies: from Networks to Models and their Representations
Journal article, 2018

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.

Modelling

Street networks

Graph representation

Author

Stephen Marshall

University College London (UCL)

Jorge Gil

Chalmers, Architecture and Civil Engineering, Urban Design and Planning

Karl Kropf

Oxford Brookes University

Martin Tomko

University of Melbourne

Lucas Figueiredo

Federal University of Paraíba

Networks and Spatial Economics

1566-113X (ISSN) 15729427 (eISSN)

Vol. 18 3 735-749

Areas of Advance

Building Futures (2010-2018)

Subject Categories

Social and Economic Geography

Infrastructure Engineering

Architecture

Information Science

Discrete Mathematics

DOI

10.1007/s11067-018-9427-9

More information

Latest update

4/5/2022 6