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Ship Trajectories Pre-processing Based on AIS Data

Published online by Cambridge University Press:  22 April 2018

Liangbin Zhao ,
Guoyou Shi  and
Jiaxuan Yang
Liangbin Zhao*
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China)
Guoyou Shi
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China)
Jiaxuan Yang
Affiliation:
(Navigation College, Dalian Maritime University, Dalian, China)
*
(E-mail: [email protected])
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Abstract

Data derived from the Automatic Identification System (AIS) plays a key role in water traffic data mining. However, there are various errors regarding time and space. To improve availability, AIS data quality dimensions are presented for detecting errors of AIS tracks including physical integrity, spatial logical integrity and time accuracy. After systematic summary and analysis, algorithms for error pre-processing are proposed. Track comparison maps and traffic density maps for different types of ships are derived to verify applicability based on the AIS data from the Chinese Zhoushan Islands from January to February 2015. The results indicate that the algorithms can effectively improve the quality of AIS trajectories.

Keywords

AIS TrajectoriesAIS errorData qualityPre-processing
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 5 , September 2018 , pp. 1210 - 1230
Copyright
Copyright © The Royal Institute of Navigation 2018 

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