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Open AccessArticle

Vessel Trajectory Reconstruction Based on Functional Data Analysis Using Automatic Identification System Data

1
Department of Civil Engineering, Chosun University, Gwangju 61452, Korea
2
Center for Built Environment (CBE), Sungkyunkwan University, Suwon-si 16419, Gyeonggi-do, Korea
3
Department of Civil Engineering, Kangwon National University, Chuncheon-si 24341, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(3), 881; https://doi.org/10.3390/app10030881
Received: 24 December 2019 / Revised: 15 January 2020 / Accepted: 21 January 2020 / Published: 28 January 2020
(This article belongs to the Special Issue Selected Papers from IMETI 2018)
This study provides an automatic shipping-route construction method using functional data analysis (FDA), which analyzes information about curves, such as multiple data points over time. The proposed approach includes two steps: outlier detection and shipping-route construction. This study uses automatic-identification system (AIS) data for the experiments. The effectiveness of the proposed method is demonstrated through case studies, wherein our approach is compared with the Mahalanobis distance method for trajectory-outlier detection, and the performance of vessel trajectory reconstruction is compared with that of a density-based approach. The proposed method improves understanding of vessel-movement dynamics, thereby improving maritime monitoring and security. View Full-Text
Keywords: map construction; shipping-route construction; functional data analysis; data depth map construction; shipping-route construction; functional data analysis; data depth
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MDPI and ACS Style

Jeong, M.-H.; Jeon, S.-B.; Lee, T.-Y.; Youm, M.K.; Lee, D.-H. Vessel Trajectory Reconstruction Based on Functional Data Analysis Using Automatic Identification System Data. Appl. Sci. 2020, 10, 881.

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