Faced with the problem of high no-load rate of urban taxi and taxi difficulty of passengers, this study analyzes the passenger hotspots for taxi drivers and taxi hotspots for passengers, and proposes a data processing model based on DBSCAN algorithm. Using this model, the GPS trajectory data of 182 taxis in Beijing are processed, and the data precision is improved. For different audiences, K-means algorithm is used to cluster the data and get the relevant hotspots. Experiments show that the proposed method can not only effectively provide taxi drivers with high probability of passenger hotspots, but also provide a feasible solution to the problem of taxi difficulty of passengers.