title: Centrality measures in spatial networks of urban streets.
abstract: 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.
authors.affiliation: Scuola Superiore di Catania, Italy.
authors.forename: Paolo
authors.initials: P
authors.lastname: Crucitti
authors.forename: Vito
authors.initials: V
authors.lastname: Latora
authors.forename: Sergio
authors.initials: S
authors.lastname: Porta