For a considerable time, researchers have focused on defining different measures capable to characterizing the importance of vertices in networks. One type of these networks, the cities, are complex systems that generate large quantity of information. These data are an important part of the characteristics of the urban network itself. Because of this, it is crucial to have a classification system, for the vertices of a network, considering the data we can find in the city itself. To address this question, this paper studies and compares several measures of centrality specifically applied to urban networks. These centralities are based on the calculation of the eigenvectors of a matrix and are very suitable for urban networks with data. With the aim of expanding the range covered by these measures, a new centrality measure is presented. Finally we compare three centralities by means of a real network and real data on the city of Rome (Italy).

在相当长的时间内，研究人员一直致力于定义能够描述网络中顶点重要性的不同度量。这些网络中的一种，即城市，是产生大量信息的复杂系统。这些数据是城市网络本身特征的重要组成部分。因此，考虑到我们可以在城市本身中找到的数据，对于网络的顶点，拥有一个分类系统至关重要。为了解决这个问题，本文研究并比较了几种专门用于城市网络的集中度测量方法。这些中心点是基于矩阵特征向量的计算，非常适用于具有数据的城市网络。为了扩大这些措施的适用范围，提出了一种新的集中性措施。