Abstract: With the rapid development of the urbanization process, the society is suffering from traffic congestion, air pollution and other urban problems caused by the large amount of human movement. This paper presents a visual analysis method, which integrates vehicle surveillance data, POI data to help analyze the human mobility patterns. The proposed method applies an improved DBSCAN algorithm, which divides geographical area into functional regions based on the POI data to enhance the hidden intention behind human movement. Furthermore, we present the distribution and differentiation of different functional regions with Bubble Set, and visually link the human mobility patterns among different functional regions. Finally, we analyze and explore the human movement intention through the case studies. The case studies are equipped with real world data and the characteristics of the functional regions to help understand the human mobility patterns.