Flow Orientation Analysis for Major Activity Regions Based on Smart Card Transit Data

Analyzing public movement in transportation networks in a city is significant in understanding the life of citizen and making improved city plans for the future. This study focuses on investigating the flow orientation of major activity regions based on smart card transit data. The flow orientation based on the real movements such as transit data can provide the easiest way of understanding public movement in the complicated transportation networks. First, high inflow regions (HIRs) are identified from transit data for morning and evening peak hours. The morning and evening HIRs are used to represent major activity regions for major daytime activities and residential areas, respectively. Second, the directional orientation of flow is then derived through the directional inflow vectors of the HIRs to show the bias in directional orientation and compare flow orientation among major activity regions. Finally, clustering analysis for HIRs is applied to capture the main patterns of flow orientations in the city and visualize the patterns on the map. The proposed methodology was illustrated with smart card transit data of bus and subway transportation networks in Seoul, Korea. Some remarkable patterns in the distribution of movements and orientations were found inside the city. The proposed methodology is useful since it unfolds the complexity and makes it easy to understand the main movement patterns in terms of flow orientation.