Abstract

Characterizing the structure of cities constitutes an important task, since the identification of similar cities can promote sharing of respective experiences. In the present work, we consider 20 European cities from 5 respective countries and with comparable populations, each of which characterized in terms of four topological as well as one geometrical feature. These cities are then mapped into respective networks by considering their pairwise similarity as gauged by the coincidence methodology, which consists of combining the Jaccard and interiority indices. The methodology incorporates a parameter alpha that can control the relative contribution of features with the same or opposite signs to the overall similarity. Interestingly, the maximum modularity cities’ network is obtained for a non-standard parameter configuration, showing that it could not be obtained were not for the adoption of the parameter alpha. The network with maximum modularity presents four communities that can be mostly related to four of the five considered countries, indicating a tendency of the cities from a same country being similar. The coincidence methodology was then applied to investigate the effect of several features combinations on the respectively obtained networks, leading to a highly modular features network containing four main communities that can be understood as the main possible models for the considered cities.

Graphical abstract

中文翻译：

---

城市和特征的相似性方法

摘要

表征城市结构是一项重要任务，因为相似城市的识别可以促进各自经验的分享。在目前的工作中，我们考虑了来自 5 个国家和具有可比人口的 20 个欧洲城市，每个城市都有四个拓扑特征和一个几何特征。然后通过考虑它们的成对相似性，将这些城市映射到各自的网络中，这种相似性由结合 Jaccard 指数和内部指数组成的巧合方法来衡量。该方法包含一个参数 alpha，该参数可以控制具有相同或相反符号的特征对整体相似性的相对贡献。有趣的是，最大模块化城市网络是针对非标准参数配置获得的，表明它无法获得不是因为采用了参数 alpha。具有最大模块化的网络呈现了四个社区，这些社区主要与五个考虑的国家中的四个国家相关，表明来自同一国家的城市有相似的趋势。然后应用巧合方法来研究几种特征组合对分别获得的网络的影响，从而形成一个高度模块化的特征网络，其中包含四个主要社区，可以理解为所考虑城市的主要可能模型。

图形概要