Centrality measures in spatial networks of urban streets.

By Paolo Crucitti, Vito Latora, Sergio Porta. Physical review. E, Statistical, nonlinear, and soft matter physics, 2005

689 citations recorded by the source corpus.

We study centrality in urban street patterns of different world cities represented as networks in geographical space. The results indicate that a spatial analysis based on a set of four centrality indices allows an extended visualization and characterization of the city structure. A hierarchical clustering analysis based on the distributions of centrality has a certain capacity to distinguish different classes of cities. In particular, self-organized cities exhibit scale-free properties similar to those found in nonspatial networks, while planned cities do not.

Subfields: Building and Construction, Statistical and Nonlinear Physics, Transportation

View Paper: https://www.semanticscholar.org/paper/cc317c3aa92fcf75a1e350ed0ffebe42ffb0d17f

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In Building and Construction

In Statistical and Nonlinear Physics

In Transportation

Citations in the corpus

Economic and social consequences of human mobility restrictions under COVID-19 (2020, background): “Efficiency is a global network measure that combines the information deriving from network cohesiveness and the distance between nodes to measure how efficiently information/individuals travel over the network (18).”
Deanonymizing mobility traces: using social network as a side-channel (2012, methodology): “For the first step, we identify landmark nodes using a node centrality measure [25, 7], which is a measure of the relative importance of a vertex within a graph.”
Spatial Science and Network Science: Review and Outcomes of a Complex Relationship (2014, background): “Notably, Crucitti et al. (2006) take into account physical distance in their calculation of node centrality, arguing that their results may be more useful to urban planning and design.”
Brain graphs: graphical models of the human brain connectome. (2011, background): “This has been done in the context of other more generally spatially embedded systems: The spatial distributions of centrality measures have been used, for example, to study urban street architectures (Crucitti et al. 2006).”
Elementary processes governing the evolution of road networks (2012, methodology): “Among the various centrality indices available for spatial networks, we use here the betweenness centrality (BC”
Cellular Traffic Offloading through WiFi Networks (2011, background): “…is a lower bound for the network performance as the speed of the current wireless network has notably increased since the publication of our cited literatures proportion with the centrality [15] of the deployed APs: as T increases, less APs are deployed around the main streets of San Francisco.”
Street Centrality and the Location of Economic Activities in Barcelona (2012, methodology): “The MCA model builds on these works by applying the measures in the spatial case of streets and intersections (Crucitti et al., 2006).”