Aiming at the long-term problems such as timeliness poor,and frequent errors and omissions in the process of artificial statistics in the capability supply level data tracking of Chinese coastal ports,we analyze the specific reasons for the distortion of traditional berth passing capacity statistics,propose to use berth utilization rate as a representation index to evaluate port service level,and make spatial topological analysis based on geographic information system(GIS) platform and automatic identification system(AIS) data coupling.Then we develop a berth utilization algorithm model based on AIS big data by comprehensively considering the influencing factors such as spatial relationship,speed characteristics and length of stay,and verify the algorithm by taking the container berth utilization rate of Shanghai Port in 2019 as an example.The results show that the proposed berth utilization algorithm model is credible.The algorithm model can provide a technical means to reflect the objective reality and quantitatively analyze and judge the port service level.It can help government departments to dynamically monitor the interactive balance relationship between port capacity and transportation demand in the long term,support government departments to make decisions on port development priorities and construction timing,and provide technical support to avoid space resource waste,redundant construction,excess capacity and other problems