2 research outputs found
Topological street-network characterization through feature-vector and cluster analysis
Complex networks provide a means to describe cities through their street
mesh, expressing characteristics that refer to the structure and organization
of an urban zone. Although other studies have used complex networks to model
street meshes, we observed a lack of methods to characterize the relationship
between cities by using their topological features. Accordingly, this paper
aims to describe interactions between cities by using vectors of topological
features extracted from their street meshes represented as complex networks.
The methodology of this study is based on the use of digital maps. Over the
computational representation of such maps, we extract global complex-network
features that embody the characteristics of the cities. These vectors allow for
the use of multidimensional projection and clustering techniques, enabling a
similarity-based comparison of the street meshes. We experiment with 645 cities
from the Brazilian state of Sao Paulo. Our results show how the joint of global
features describes urban indicators that are deep-rooted in the network's
topology and how they reveal characteristics and similarities among sets of
cities that are separated from each other.Comment: Paper to be published on the International Conference on
Computational Science (ICCS), 201