Frequent Commuting Associated Zone Identification: A Case Study in Beijing, China Based on Floating Vehicle Data

The movement of residents enables social, economic, and cultural exchanges. The frequent commuting association between two zones is an outward manifestation of the intricate inter‐zonal social, economic and cultural association. Detecting the frequent commuting associations can not only assist the functional mapping but help local government alleviate jobs‐housing imbalance and optimize public transportation routes. Given the inadequacy of current definitions in quantitative description, we propose a new concept of frequent commuting associated zone (FCAZ) to represent the inter‐zonal frequent commuting association and a self‐organized data mining method for identification. The spatial extent of FCAZ is generated using a self‐organized integration method considering the spatial–temporal proximity and similarity of the frequent building couples. The internal heterogeneity of the association strength is expressed and mined through an iterative growth algorithm that aggregates adjacent building couples with different association strengths. The floating vehicle data of Beijing is used to mine the FCAZs and analyze residential commuting patterns. The detected FCAZs show an uneven spatial distribution. The functional categories of the FCAZs align with the commuting behaviors of the residents leaving for work or school in the morning and returning home or having a night out in the evening.