Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, Brazil.
Universidade Federal de São Paulo (UNIFESP), São José dos Campos, Brazil.
PLoS One. 2021 Mar 10;16(3):e0248126. doi: 10.1371/journal.pone.0248126. eCollection 2021.
Topological analysis and community detection in mobility complex networks have an essential role in many contexts, from economics to the environmental agenda. However, in many cases, the dynamic component of mobility data is not considered directly. In this paper, we study how topological indexes and community structure changes in a business day. For the analyzes, we use a mobility database with a high temporal resolution. Our case study is the city of São José dos Campos (Brazil)-the city is divided into 55 traffic zones. More than 20 thousand people were asked about their travels the day before the survey (Origin-Destination Survey). We generated a set of graphs, where each vertex represents a traffic zone, and the edges are weighted by the number of trips between them, restricted to a time window. We calculated topological properties, such as degree, clustering coefficient and diameter, and the network's community structure. The results show spatially concise community structures related to geographical factors such as highways and the persistence of some communities for different timestamps. These analyses may support the definition and adjustment of public policies to improve urban mobility. For instance, the community structure of the network might be useful for defining inter-zone public transportation.
复杂移动网络中的拓扑分析和社区检测在许多领域都具有重要作用，从经济学到环境议程等。然而，在许多情况下，移动数据的动态组件并没有被直接考虑。在本文中，我们研究了商业日中拓扑指标和社区结构的变化。为此，我们使用具有高时间分辨率的移动性数据库进行分析。我们的案例研究是巴西圣若泽·多斯坎波斯市（São José dos Campos）——该市被划分为 55 个交通区。在调查前一天，我们询问了超过 2 万名市民的出行情况（出行目的地调查）。我们生成了一组图，其中每个顶点代表一个交通区，边的权重由它们之间的旅行次数决定，并限制在一个时间窗口内。我们计算了拓扑属性，如度数、聚类系数和直径，以及网络的社区结构。结果显示，社区结构在空间上具有紧凑性，与高速公路等地理因素以及一些社区在不同时间戳的持续存在有关。这些分析可以支持公共政策的制定和调整，以改善城市交通。例如，网络的社区结构可以用于定义区域间的公共交通。
