Journal of Ocean Engineering and Technology (한국해양공학회지)

Korean Society of Ocean Engineers (한국해양공학회)
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Validation of OpenDrift-Based Drifter Trajectory Prediction Technique for Maritime Search and Rescue

  • Received : 2023.06.14
  • Accepted : 2023.06.27
  • Published : 2023.08.31
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Abstract

Due to a recent increase in maritime activities in South Korea, the frequency of maritime distress is escalating and poses a significant threat to lives and property. The aim of this study was to validate a drift trajectory prediction technique to help mitigate the damages caused by maritime distress incidents. In this study, OpenDrift was verified using satellite drifter data from the Korea Hydrographic and Oceanographic Agency. OpenDrift is a Monte-Carlo-based Lagrangian trajectory modeling framework that allows for considering leeway, an important factor in predicting the movement of floating marine objects. The simulation results showed no significant differences in the performance of drift trajectory prediction when considering leeway using four evaluation methods (normalized cumulative Lagrangian separation, root mean squared error, mean absolute error, and Euclidean distance). However, leeway improved the performance in an analysis of location prediction conformance for maritime search and rescue operations. Therefore, the findings of this study suggest that it is important to consider leeway in drift trajectory prediction for effective maritime search and rescue operations. The results could help with future research on drift trajectory prediction of various floating objects, including marine debris, satellite drifters, and sea ice.

Keywords

Acknowledgement

This research was partially supported by the Korea Institute of Marine Science & Technology Promotion (KIMST), which is funded by the Korea Coast Guard (20220463), and by the Korea Evaluation Institute of Industrial Technology (KEIT) grant, which is funded by the Korean government (KCG, MOIS, NFA) [RS-2022-001549812, Development of technology to respond to marine fires and chemical accidents using wearable devices].

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