Abstract: The existing community discovery methods usually focus on urban areas as research objects, exploring the spatial interaction relationships between hotspot areas. However, there are certain limitations in expressing the correlation between OD (origin destination) pairs, making it challenging to conduct urban community structure discovery for OD pairs. Therefore, this paper proposes an urban community discovery method that integrates trajectory representations based on the line graph. First, a traditional spatial interaction network is constructed based on travel trajectory data. Then, the nodes and edges of the traditional topological graphs are exchanged to establish a new trajectory interaction topology graph from the perspective of a line graph with OD pair features as nodes and starting points and end points of the OD flow as edges. Finally, this paper uses a community discovery algorithm that considers node attributes and network topology to discover urban communities based on the trajectory interactive topological graph. Furthermore, a visual analytics system is designed for urban community discovery from the line graph perspective, which helps users explore urban sub-regions that can reflect people’s real activity space, and provides reference for urban management. The practicality and effectiveness of the proposed method and system have been demonstrated through two case studies and user evaluation experiments.