## 5 Results and Discussion
### Clustering Results  
Based on a set of grid-level indicators and hierarchical clustering analysis, we explored the functional similarities and differences in freight-related roles across various urban regions. Figure 7 presents a heatmap of the clustering results, with all grid cells grouped into six distinct clusters through a dendrogram-guided process. The spatial distribution of these clusters is visualized in Figure 8, allowing for a detailed interpretation of the freight-oriented functional roles associated with each cluster. Cluster 1: Core Logistics Hubs. Comprising 12.5% of the total grid cells yet accounting for 51.6% of all freight trips, this cluster is characterized by exceptionally high and stable trip volumes, a concentrated distribution of vehicle types (low vehicle-type entropy), and moderately sized fleets (medium ID entropy). Spatially, this cluster encompasses critical freight infrastructure, such as Yangshan Port and Waigaoqiao Port, and industrial logistics nodes, like Jiading Automotive Hub and the Lingang Area. These grids represent highly specialized freight centers that dominate bulk commodity transportation and vertically integrated supply chain operations, reflecting a high level of scale efficiency and process standardization. Figure 7: Heatmap of clustering result. Numbers denote cluster group; each row represents a grid cell, and each column corresponds to a regional indicator. Cluster 2: Peripheral Support Zones. Representing 24.8% of grids and generating 31.3% of total freight trips, these zones are spatially adjacent to the core logistics hubs and function as auxiliary nodes. Serving as transitional areas between high-intensity freight areas and residential-commercial zones, they exhibit medium levels of vehicle-type entropy and ID entropy, reflecting a hybrid pattern of \"hub specialization\" and \"distribution diversification\". Influenced by the spillover effects from the core hubs, they also display a relatively high trip intensity. Cluster 3: Mono-functional Dominant Areas. This cluster is defined by the lowest vehicle-type entropy and the highest daily fluctuation in trip volumes, indicating domination by a single vehicle type and significant temporal variability. ID entropy within this cluster varies widely across cells. Spatially, these grids are concentrated near the Pudong Resource Recycling Base, the Chongming ecological conservation area, and coastal zones, with scattered presence across the rest of the city. These areas are likely associated with highly specialized freight operations such as construction waste transport and resource recovery logistics. Cluster 4: Integrated Urban Distribution Zones. Accounting for 38.5% of the grid cells yet only 10.3% of freight trips, this is the largest cluster in terms of area. These grids feature low overall trip volumes, high vehicle-type entropy (indicating mixed vehicle usage), and moderate ID entropy, suggesting relatively stable delivery relationships. Spatially, these zones are widely dispersed in a clustered manner across residential neighborhoods, commercial areas, and low-intensity industrial zones. They are primarily engaged in routine consumer deliveries and micro-enterprise freight, characterized by diverse product types, effectively forming the \"capillaries\" of the urban freight system. Cluster 5: Nighttime-Dominated Freight Zones. Comprising 7.1% of the grid cells and 1.8% of trips, this cluster is distinguished by its exceptionally high share of nighttime trips. Shaped by Shanghai's freight vehicle access restrictions during daytime hours, these zones are concentrated within the outer ring road area, where truck bans are in effect. Additionally, scattered grids of this type are found outside the outer ring, possibly related  
Figure 8: Spatial distribution of clustered grid cells, with colors representing the results of hierarchical clustering. to trip destinations within restricted areas or specific production schedules.