Network structure and city size.

Network structure varies across cities. This variation may yield important knowledge about how the internal structure of the city affects its performance. This paper systematically compares a set of surface transportation network structure variables (connectivity, hierarchy, circuity, treeness, entr...

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Main Author: David Levinson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3257243?pdf=render
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spelling doaj-f4c1b311327a4d0798ffe0b691b9862d2020-11-25T01:42:29ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0171e2972110.1371/journal.pone.0029721Network structure and city size.David LevinsonNetwork structure varies across cities. This variation may yield important knowledge about how the internal structure of the city affects its performance. This paper systematically compares a set of surface transportation network structure variables (connectivity, hierarchy, circuity, treeness, entropy, accessibility) across the 50 largest metropolitan areas in the United States. A set of scaling parameters are discovered to show how network size and structure vary with city size. These results suggest that larger cities are physically more inter-connected. Hypotheses are presented as to why this might obtain. This paper then consistently measures and ranks access to jobs across 50 US metropolitan areas. It uses that accessibility measure, along with network structure variables and city size to help explain journey-to-work time and auto mode share in those cities. A 1 percent increase in accessibility reduces average metropolitan commute times by about 90 seconds each way. A 1 percent increase in network connectivity reduces commute time by 0.1 percent. A 1 percent increase in accessibility results in a 0.0575 percent drop in auto mode share, while a 1 percent increase in treeness reduces auto mode share by 0.061 percent. Use of accessibility and network structure measures is important for planning and evaluating the performance of network investments and land use changes.http://europepmc.org/articles/PMC3257243?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author David Levinson
spellingShingle David Levinson
Network structure and city size.
PLoS ONE
author_facet David Levinson
author_sort David Levinson
title Network structure and city size.
title_short Network structure and city size.
title_full Network structure and city size.
title_fullStr Network structure and city size.
title_full_unstemmed Network structure and city size.
title_sort network structure and city size.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2012-01-01
description Network structure varies across cities. This variation may yield important knowledge about how the internal structure of the city affects its performance. This paper systematically compares a set of surface transportation network structure variables (connectivity, hierarchy, circuity, treeness, entropy, accessibility) across the 50 largest metropolitan areas in the United States. A set of scaling parameters are discovered to show how network size and structure vary with city size. These results suggest that larger cities are physically more inter-connected. Hypotheses are presented as to why this might obtain. This paper then consistently measures and ranks access to jobs across 50 US metropolitan areas. It uses that accessibility measure, along with network structure variables and city size to help explain journey-to-work time and auto mode share in those cities. A 1 percent increase in accessibility reduces average metropolitan commute times by about 90 seconds each way. A 1 percent increase in network connectivity reduces commute time by 0.1 percent. A 1 percent increase in accessibility results in a 0.0575 percent drop in auto mode share, while a 1 percent increase in treeness reduces auto mode share by 0.061 percent. Use of accessibility and network structure measures is important for planning and evaluating the performance of network investments and land use changes.
url http://europepmc.org/articles/PMC3257243?pdf=render
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