Multi-remote sensing of spilled oils from A Symphony tanker collision in the Yellow Sea
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摘要: 溢油是海洋生态环境监测的重点对象。合成孔径雷达、光学遥感与热红外遥感等卫星技术开展海洋溢油监测的机理已得到阐明，发挥多源遥感的技术特点和应用优势，实现海洋溢油的精准监测与量化评估，为海洋环境保护提供重要的技术支撑。2021年4月27日巴拿马籍“义海”轮与利比亚籍“交响乐”油轮在青岛外海发生碰撞，导致约
9400 t船载货油泄漏入海。本文利用多源卫星遥感数据，监测并分析了该事故海域的溢油污染覆盖状况及其乳化溢油分布特征。基于溢油多源遥感响应机理与响应特征，优化了多源卫星遥感数据的处理流程，实现了溢油覆盖区域的识别与多种溢油污染类型的分类。结果表明：2021年5月1日至5月22日，“交响乐”轮溢油污染事件累积溢油像元覆盖面积为2368.7 km2，其中乳化溢油像元覆盖面积为1019.3 km2，乳化油面积占比达43.0%，单日最大溢油像元面积达734 km2；多源遥感监测结果可以互为验证，光学遥感更具备识别不同溢油污染的能力，其中乳化溢油代表了污染危害的关键所在，从而提高了海洋溢油污染的监测评估精度，为溢油污染事件的危害评估与精细化监测提供可靠的技术与方法参考。Abstract: Oil spill is one of the critical target of marine environmental monitoring. Synthetic Aperture Radar (SAR), thermal infrared remote sensing, and optical remote sensing for monitoring of marine oil spills have been elucidated, and it is crucial for marine environmental protection to utilize the features and advantages of multi-source remote sensing to achieve accurate monitoring and quantitative assessment of marine oil spills. On April 27, 2021, the collision between the Panamanian vessel Sea Justice and the Liberian oil tanker A Symphony resulted in an estimated 9400 t of cargo oil seeping into the sea. Here, we monitor and analyze the oil spill pollution coverage and emulsified oil spill characteristics in this accident using multi-source satellite remote sensing data. Based on the response mechanism and characteristics of oil spill multi-source remote sensing, the processing of multi-source data is optimized to realize the identification of oil spill and the classification of multiple oil spill types. The findings indicate that from May 1 to May 22, 2021, the cumulative pixel coverage area of oil spills from A Symphony tanker was2368.7 km2, of which the emulsified oil pixel coverage area was1019.3 km2, accounting for 43.0%. The maximum daily oil spill pixel area reached 734 km2. The results of multi-remote sensing monitoring mutually validated each other, and optical remote sensing is more capable of identifying different oil spill pollution, in which the emulsified oil represents the key of pollution hazards. It improves the accuracy of monitoring and assessment of marine oil spill pollution, and provides reliable technical and methodological references for the hazard assessment and refined monitoring of oil pollution events. -
图 1 “交响乐”轮溢油事件研究区域
a. “交响乐”轮碰撞点及溢油污染最大覆盖范围；b. 5月1日13时18分研究区域内HY-1D CZI传感器观测结果, 研究区域内首次发现溢油痕迹；c. 5月25日10时41分研究区域内HY-1 C CZI传感器观测结果, 研究区域内已无明显溢油；d，e. 分别对应图b和c中白色虚线区域，d为海面低风速区，e可观察到“交响乐”轮及明显的海面溢油
Fig. 1 Study area for A Symphony tanker collision event
a. Collision point of A Symphony tanker and maximum coverage of oil spill pollution; b. the HY-1D CZI image at 13:18 on 1 May, and oil spill traces were first discovered in the study area; c. the HY-1C CZI image at 10:41 on 25 May, and no apparent oil spill was observed in the study area; d and e correspond to the white dashed areas in b and c, respectively; d is a low-wind zone on the sea surface; e shows A Symphony tanker and the obvious oil spill traces
图 2 2021年4月27日至5月22日“交响乐”轮碰撞事件时间线及多源卫星遥感数据
Fig. 2 Timeline of A Symphony tanker collision event from April 27 to May 22, 2021 with corresponding multi- remote sensing data
图 3 多源遥感数据溢油定量监测处理流程
Fig. 3 Flow chart for quantitative oil spill monitoring of multi-source remote sensing data
图 4 光学遥感数据在不同耀光条件下的溢油响应特征
a1、b1、c1. 5月21日准同步Sentinel-2（S2A） MSI（R：655 nm,，G：560 nm，B：492 nm），HJ-2（R：660 nm，G：560 nm，B：470 nm），HY-1 C（R：650 nm，G：560 nm，B：460 nm）光学真彩色合成数据；a2、b2、c2. 不同传感器油膜反射率特征差异；a3、b3、c3. 溢油光学识别分类结果
Fig. 4 Oil spill response characteristics of optical remote sensing under different sunglint conditions
a1, b1, c1. Quasi-synchronous Sentinel-2 (S2A) MSI (R: 655 nm, G: 560 nm, B: 492 nm), HJ-2 (R: 660 nm, G: 560 nm, B: 470 nm) and HY-1C (R: 650 nm, G: 560 nm, B: 460 nm) optical true-color composite data from May 21; a2, b2, c2. differences in reflectance characteristics of oil films for different sensors; a3, b3, c3. optical identification and classification of oil spill
图 5 多源遥感数据的光学与SAR溢油响应特征
a1、b1、c1、d1. 5月2日准同步HY-1 D（R：650 nm，G：560 nm，B：460 nm），HJ-2（R：660 nm，G：560 nm，B：470nm），GF-1（R：660 nm，G：555 nm，B：485 nm）光学真彩色合成数据及GF-3 SAR数据；a2、b2、c2、d2. 溢油识别分类结果
Fig. 5 Oil spill response characteristics of optical remote sensing and SAR
a1, b1, c1, d1. Quasi-simultaneous HY-1D (R: 650 nm, G: 560 nm, B: 460 nm), HJ-2 (R: 660 nm, G: 560 nm, B: 470 nm) and GF-1 (R: 660 nm, G: 555 nm, B: 485 nm) optical true-color composites and GF-3 on May 2 SAR data; a2, b2, c2, d2. identification and classification of oil spill in a1, b1, c1, d1
图 6 Landsat 8 光学数据及热红外数据的溢油响应特征
a1. 5月13日Landsat 8 OLI（R：655 nm，G：563 nm，B：483 nm）光学真彩色合成数据；b1. 5月22日Landsat 8 OLI光学真彩色合成数据；c1. 5月13日Landsat 8 TIRS热红外数据；d1. 5月22日Landsat 8 TIRS热红外数据；a2、b2、c2、d2. 溢油识别分类结果
Fig. 6 Oil spill response characteristics of Landsat 8 optical and thermal infrared data
a1. Landsat 8 OLI (R: 655 nm, G: 563 nm, B: 483 nm) optical true-color composite data on 13 May; b1. Landsat 8 OLI optical true-color composite data on 22 May; c1. Landsat 8 TIRS thermal infrared data on 13 May; d1. Landsat 8 TIRS thermal infrared data on 22 May; a2, b2, c2, d2. identification and classification of oil spill in a1, b1, c1, d1
图 7 基于多源遥感数据的识别分类结果
Fig. 7 Identification and classification of oil spill based on multi-remote sensing data
图 8 “交响乐”轮溢油像元面积统计结果
Fig. 8 Statistical results of pixel area of oil spill for A Symphony tanker
图 9 a. Sentinel-2 MSI光学真彩色合成数据及采样点分布；b. 光谱响应特征；c. 溢油识别提取结果；d. 乳化油归一化浓度估算结果
Fig. 9 a. Optical true-color composite of Sentinel-2 MSI and sampling sites distribution; b. spectral response characteristics; c. Identification and classification of oil spill; d. the estimation of emulsified normalized oil concentration
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