Research on Extraction Method of Multiple Narrow Channel Vessel Trajectory Feature in Yangtze River Based on VITS Data

Vessel big data play a significant role in understanding vessel behaviors and thus facilitating the prosperity of waterway transportation. However, relevant research regarding trajectory recognition broad range narrow channels still lacks, especially using VITS data. The major objective this paper is to conduct analysis based on novel examine its availability inland An alternate aim develop more comprehensive framework extract multiple waterways. This utilized information belonging Yangtze River captured by VITS. Four compression algorithms were conducted. Additionally, performances three clustering approaches evaluated. Speed distribution was also implemented. results indicated that slide window (SW) algorithm outperforms other counterparts. Relative DBSCAN, K-means hierarchical (HCA) tend be capable balanced classification. first utilize feature extraction can potentially provide useful insight for channels.