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A new ship tracing technology from oil spills based on multi-source data.
Luo, Dan; Chen, Peng; Yang, Jingsong; Chen, Xin; Li, Xiunan; Zheng, Gang; Ren, Lin; Zhao, Yizhi.
Affiliation
  • Luo D; Ocean College, Zhejiang University, Zhoushan 316021, China; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
  • Chen P; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China. Electronic address: chenpeng@sio.org.cn.
  • Yang J; Ocean College, Zhejiang University, Zhoushan 316021, China; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, Chi
  • Chen X; School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Li X; Ocean College, Zhejiang University, Zhoushan 316021, China; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
  • Zheng G; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
  • Ren L; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
  • Zhao Y; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
Mar Pollut Bull ; 207: 116808, 2024 Aug 14.
Article in En | MEDLINE | ID: mdl-39146713
ABSTRACT
Oil spill from ship can cause serious pollution to the Marine environment, but it is very difficult to find and confirm the troublemaker. In order to determine the oil spill ship, this paper proposes a new method to trace the source of ship oil spills and find the suspected ship that spills oil based on SAR imagery, AIS data and related marine environment data. First, we filter AIS data based on position of oil spill areas on remote sensing imagery and convert oil spill areas into trajectory points. Secondly, based on the Lagrangian particle motion model, a bidirectional drift model is proposed to calculate the average similarity between the forward and backward drift results. Finally, the most likely oil spill ship is determined according to the average similarity results. The results of the case study show that the method is effective and practical.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Mar Pollut Bull Year: 2024 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Mar Pollut Bull Year: 2024 Document type: Article Affiliation country: China