Navigational risk analysis based on GIS spatiotemporal trajectory mining: a case study in Nanjing Yangtze River Bridge waters

Abstract

With the continuous growth of the quantity, scale, and speed of vessels in recent years, maritime accidents are posing increasing risks to societies and individuals, especially in narrow inland waterways. Therefore, it is of great significance to analyze navigational risks to ensure the safety of waterborne transportation. In this paper, the navigational risks of Nanjing Yangtze River Bridge (NYRB) waters are investigated based on spatiotemporal mining on massive automatic identification system (AIS) trajectories by using geographic information system (GIS) techniques. A time-series-oriented trajectory processing method is proposed to deal with the historical AIS data in the whole year of 2019. The method adopts a periodic processing strategy to produce traffic density estimation products in multiple temporal scales for supporting spatiotemporal analysis. The proposed method greatly improves the data-processing efficiency and provides a flexible way to deeply understand the vessel behavior patterns in NYRB waters. Then the complete characteristics of the spatial distribution and temporal variation of AIS trajectories are revealed. Based on that, three types of critical navigational risks are discovered, which include the safety distance risk, the pier collision risk, and the traffic congestion risk. Moreover, we find that the greatest risk is existed in small vessels in the flood season, which is worth the most concern.