## 2 Community Detection across Space and Its Variation across Time
### Community Detection across Space
#### 2.2.2 Algorithm
From the morning rush hour to the noon rush hour, the volume of trajectory flow increased substantially and some new links emerged in local regions. This implies that the interactions between land uses in the noon rush hour are more intense than in the morning rush hour. From the noon rush hour to the evening rush hour, the interactions decreased not only through the main roads but also across the western areas. The obvious feature of interactions at midnight is that there were significant connections to or from recreational land (i.e., the eastern area). Besides the connectivity property, the spatially embedded network can also imply the aggregation patterns of land uses in the functional space. The land uses that have a strong connectivity relationship in the network traffic flow tend to be grouped together (Figure 7), and, in this way, we can explore the city structure and transport system using the resulting clustering patterns of land uses. Figure 7: Communities in different time periods with cell size k = 1000 m: (**a**) morning rush hour; (**b**) noon rush hour; (**c**) evening rush hour; (**d**) midnight. As presented in Figure 7, we classified the land uses into eight communities and there were some cells with no nodes. This is because there were no trajectory flows traversing across these cells. In addition, the land uses in the same community do not have to be contiguous in space. The reason is that our study aimed to cluster land uses from the perspective of their transport function, and the final similarity of the nodes was decided by both their attractive degree and structure similarity, which were calculated based on the spatially embedded network. Some neighboring land uses could have a low similarity due to their weak connectivity in the spatially embedded network, and some distant land uses could be grouped together if they are connected by a route with large traffic flows. More specifically, as presented in Figure 7a, the study region in the morning rush hour was partitioned into five main communities, in each of which the land uses had a strong transport connection. Such relations also imply the actual aggregation of human activities and urban functions, e.g., the business district in the eastern part, the residential area in the southern part, and the universities in the northern area. In addition, there were four main communities in the noon rush hour. The most significant feature in this time period was that many communities were non-contiguous, or spanned multiple regions. For example, the community labeled by blue dots spanned the northern area (i.e., universities and high-technology regions) and the southern area (i.e., business districts and railway stations). In this time period, the traffic connection between distant land uses became stronger and cross-regional human activities were more frequent. In the period of the evening rush hour, the city was partitioned into two main communities which correspond to interactions among the residential areas, business districts, and universities. The small part (pink dots) corresponded to the connection between residential areas and train station areas. At midnight, there were four main communities, in which the large volume of traffic flows was directed for entertainment (e.g., bar). For example, the central Hohai entertainment area (green dots) attracted most of the neighboring land uses. We then used the GSMM method to quantify the similarity between community structures in different time periods. In such a way, we were able to find out the degree to which the transport system changed across time. As presented in Figure 8, the GSMM measure values were calculated at the macro level rather than the micro level. First, it can be observed that community structures in successive time periods usually had a high similarity. For example, the community similarities in the successive time slices of [4:00-8:00], [11:00-14:00], and [15:00-18:00] were higher than those in non-successive time slices.