For hinterland regions with developed water channels and networks, inland shipping plays a significant role in the comprehensive transportation of waterway containers. This paper extracted vessel speed from a VITS dataset with the data capacity reaching 79.7G to analyze the temporal speed distribution pattern. Entropy-TOPSIS method was utilized in this article for more specific and intuitive reflection of speed index of different periods in a day. Through integrating Entropy and TOPSIS algorithms, speed indexes were quantitatively calculated. The results revealed that vessels tended to maintain a relatively higher speed at 7:00-18:00 interval, which is consistent with working hours for Southern areas in China. The method proposed to consider speed distribution in temporal dimension is novel in this article, and it can be used for future research to measure if the temporal traffic density is of stability to provide theoretical supports for the plan, decision and management of waterway transportation.

VITS data;temporal speed distribution;Entropy-TOPSIS method;inland shipping