An Overview: Maritime Spatial-Temporal Trajectory Mining

Abstract

In recent years, the sources of maritime spatial-temporal trajectory data have been increasing. With the widespread application of detection equipment such as radars, ship-based platforms, and satellite, maritime trajectory data has shown feature of volume, variety, velocity and valueless. The increase in data types and amount of data has led to complexity and difficulty of data processing. Traditional data mining algorithms are facing serious difficulty. This paper reviews researches for maritime spatial-temporal trajectory mining in recent years on trajectory clustering, anomaly detection, and trajectory prediction. Difficulties current researches faced are pointed out and prospects of deep learning are discussed in this paper.