Street Network Studies: from Networks to Models and their Representations

Stephen Marshall (), Jorge Gil (), Karl Kropf (), Martin Tomko () and Lucas Figueiredo ()
Additional contact information
Stephen Marshall: University College London (UCL)
Jorge Gil: Chalmers University of Technology
Karl Kropf: Oxford Brookes University
Martin Tomko: The University of Melbourne
Lucas Figueiredo: Universidade Federal da Paraíba (UFPB)

Networks and Spatial Economics, 2018, vol. 18, issue 3, No 15, 735-749

Abstract: Abstract 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.

Keywords: Street networks; Modelling; Graph representation (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)

Downloads: (external link)
http://link.springer.com/10.1007/s11067-018-9427-9 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:netspa:v:18:y:2018:i:3:d:10.1007_s11067-018-9427-9

Ordering information: This journal article can be ordered from
http://www.springer. ... ce/journal/11067/PS2

DOI: 10.1007/s11067-018-9427-9

Access Statistics for this article

Networks and Spatial Economics is currently edited by Terry L. Friesz

More articles in Networks and Spatial Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().