TY - JOUR
T1 - A dynamic adaptive grating algorithm for AIS-based ship trajectory compression
AU - Ji, Yuanyuan
AU - Qi, Le
AU - Balling, Robert
N1 - Publisher Copyright:
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Royal Institute of Navigation.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - dynamic adaptive threshold
KW - grating algorithm
KW - ship trajectory
KW - vector data compression
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U2 - 10.1017/S0373463321000692
DO - 10.1017/S0373463321000692
M3 - Article
AN - SCOPUS:85187939313
SN - 0373-4633
VL - 75
SP - 213
EP - 229
JO - Journal of Navigation
JF - Journal of Navigation
IS - 1
ER -