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.
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
Mar Pollut Bull. 2024 Oct;207:116808. doi: 10.1016/j.marpolbul.2024.116808. Epub 2024 Aug 14.
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.
船舶溢油会对海洋环境造成严重污染，但很难找到并确认肇事船只。为了确定溢油船舶，本文提出了一种基于 SAR 图像、AIS 数据和相关海洋环境数据来追溯船舶溢油源并找到疑似溢油船舶的新方法。首先，我们根据遥感图像上的溢油区域位置对 AIS 数据进行过滤，并将溢油区域转换为轨迹点。其次，基于拉格朗日粒子运动模型，提出了一种双向漂移模型来计算正向和反向漂移结果之间的平均相似度。最后，根据平均相似度结果确定最有可能的溢油船舶。案例研究结果表明，该方法是有效和实用的。
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