A dynamic adaptive grating algorithm for AIS-based ship trajectory compression

Yuanyuan Ji, Le Qi, Robert Balling

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Automatic identification system (AIS)-based ship trajectory data are important for analysing maritime activities. As the data accumulate over time, trajectory compression is needed to alleviate the pressure of data storage, migration and usage. The grating algorithm, as a vector data compression algorithm with high compression performance and low computation complexity, has been considered as a very promising approach for ship trajectory compression. This algorithm needs the threshold to be set for each trajectory which limits the applicability over a large number of different trajectories. To solve this problem, a dynamic adaptive threshold grating compression algorithm is developed. In this algorithm, the threshold for each trajectory is dynamically generated using an effective approaching strategy. The developed algorithm is tested with a complex trajectory dataset from the Qiongzhou Strait, China. In comparison with the traditional grating method, our algorithm has improved advantages in the ease of use, the applicability to different trajectories and compression performance, all of which can better support relevant applications, such as ship trajectory data storage and rapid cartographic display.

Original languageEnglish (US)
Pages (from-to)213-229
Number of pages17
JournalJournal of Navigation
Volume75
Issue number1
DOIs
StatePublished - 2022

Keywords

  • dynamic adaptive threshold
  • grating algorithm
  • ship trajectory
  • vector data compression

ASJC Scopus subject areas

  • Oceanography
  • Ocean Engineering

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