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Mapping Global Shipping Density from AIS Data

Published online by Cambridge University Press:  06 June 2016

Lin Wu*
Affiliation:
(Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China) (University of Chinese Academy of Sciences, Beijing, China)
Yongjun Xu
Affiliation:
(Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)
Qi Wang
Affiliation:
(Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)
Fei Wang
Affiliation:
(Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China) (University of Chinese Academy of Sciences, Beijing, China)
Zhiwei Xu
Affiliation:
(Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)
*

Abstract

Mapping global shipping density, including vessel density and traffic density, is important to reveal the distribution of ships and traffic. The Automatic Identification System (AIS) is an automatic reporting system widely installed on ships initially for collision avoidance by reporting their kinematic and identity information continuously. An algorithm was created to account for errors in the data when ship tracks seem to ‘jump’ large distances, an artefact resulting from the use of duplicate identities. The shipping density maps, including the vessel and traffic density maps, as well as AIS receiving frequency maps, were derived based on around 20 billion distinct records during the period from August 2012 to April 2015. Map outputs were created in three different spatial resolutions: 1° latitude by 1° longitude, 10 minutes latitude by 10 minutes longitude, and 1 minute latitude by 1 minute longitude. The results show that it takes only 56 hours to process these records to derive the density maps, 1·7 hours per month on average, including data retrieval, computation and updating of the database.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2016 

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