Multi-remote sensing of spilled oils from A Symphony tanker collision in the Yellow Sea

Zhao Wei; Wang Lifeng; Niu Shengli; Lv Hang; Song Shuxian; Jiao Junnan; Song Qingjun; Lu Yingcheng

Article Contents

Article Navigation > Haiyang Xuebao > 2024 > Accepted Manuscript

Zhao Wei，Wang Lifeng，Niu Shengli, et al. Multi-remote sensing of spilled oils from A Symphony tanker collision in the Yellow Sea[J]. Haiyang Xuebao，2024, 46(x)：1–11

Citation:

Zhao Wei，Wang Lifeng，Niu Shengli, et al. Multi-remote sensing of spilled oils from A Symphony tanker collision in the Yellow Sea[J]. Haiyang Xuebao，2024, 46(x)：1–11

Citation:

Zhao Wei，Wang Lifeng，Niu Shengli, et al. Multi-remote sensing of spilled oils from A Symphony tanker collision in the Yellow Sea[J]. Haiyang Xuebao，2024, 46(x)：1–11

PDF( 4906 KB)

Multi-remote sensing of spilled oils from A Symphony tanker collision in the Yellow Sea

Zhao Wei^{1, 2
,},
Wang Lifeng³,
Niu Shengli^{1, 2},
Lv Hang³,
Song Shuxian³,
Jiao Junnan³,
Song Qingjun^{1, 2},
Lu Yingcheng^{3
,
,}

1.
National Satellite Ocean Application Service, Beijing 100081, China
2.
Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources of the People’s Republic of China, Beijing 100081, China
3.
International Institute for Earth System Science, Nanjing University, Nanjing 210023, China)

Received Date: 2023-10-25
Accepted Date: 2024-08-12

Available Online: 2024-08-15

Abstract

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 9,400 tons 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 was 2368.7 km², of which the emulsified oil pixel coverage area was 1019.3 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.
- Marine oil spill,
- oil emulsion,
- multi- remote sensing,
- A Symphony tanker,
- optical remote sensing,
- thermal infrared remote sensing

FullText(HTML)

References(39)

References

[1]	Crone T J, Tolstoy M. Magnitude of the 2010 Gulf of Mexico oil leak[J]. Science, 2010, 330(6004): 634. doi: 10.1126/science.1195840
[2]	Leifer I, Lehr W J, Simecek-Beatty D, et al. State of the art satellite and airborne marine oil spill remote sensing: application to the BP Deepwater Horizon oil spill[J]. Remote Sensing of Environment, 2012, 124: 185−209. doi: 10.1016/j.rse.2012.03.024
[3]	曹阳. 海上油污损害的救济途径研究——以墨西哥湾漏油事件为例[D]. 大连: 大连海事大学, 2014. Cao Yang. On remedies of ocean oil damage – A case study of the Gulf of Mexico oil spill[D]. Dalian: Dalian Maritime University, 2014.
[4]	Dong Yanzhu, Liu Yongxue, Hu Chuanmin, et al. Chronic oiling in global oceans[J]. Science, 2022, 376(6599): 1300−1304. doi: 10.1126/science.abm5940
[5]	Kvenvolden K A, Cooper C K. Natural seepage of crude oil into the marine environment[J]. Geo-Marine Letters, 2003, 23(3): 140−146.
[6]	Zhong Zhixia, You Fengqi. Oil spill response planning with consideration of physicochemical evolution of the oil slick: a multiobjective optimization approach[J]. Computers & Chemical Engineering, 2011, 35(8): 1614−1630.
[7]	Lu Yingcheng, Tian Qingjiu, Wang Xinyuan, et al. Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China[J]. International Journal of Digital Earth, 2013, 6(1): 76−93. doi: 10.1080/17538947.2012.695404
[8]	马媛, 高振会, 杨应斌, 等. 海上石油开采导致生态环境变化实例研究[J]. 海洋学报, 2005, 27(5): 54−59. doi: 10.3321/j.issn:0253-4193.2005.05.008 Ma Yuan, Gao Zhenhui, Yang Yingbin, et al. Eco-environment changes in the Chengbei Oil Field due to the marine petroleum exploration[J]. Hauyang Xuebao, 2005, 27(5): 54−59. doi: 10.3321/j.issn:0253-4193.2005.05.008
[9]	沈南南, 李纯厚, 王晓伟. 石油污染对海洋浮游生物的影响[J]. 生物技术通报, 2006(S1): 95−99. doi: 10.3969/j.issn.1002-5464.2006.z1.021 Shen Nannan, Li Chunhou, Wang Xiaowei. Effects of oil pollution on marine planktons[J]. Biotechnology Bulletin, 2006(S1): 95−99. doi: 10.3969/j.issn.1002-5464.2006.z1.021
[10]	Fingas M F, Brown C E. Review of oil spill remote sensing[J]. Spill Science & Technology Bulletin, 1997, 4(4): 199−208.
[11]	Brekke C, Solberg A H S. Oil spill detection by satellite remote sensing[J]. Remote Sensing of Environment, 2005, 95(1): 1−13. doi: 10.1016/j.rse.2004.11.015
[12]	Zhang Biao, Perrie W, Li Xiaofeng, et al. Mapping sea surface oil slicks using RADARSAT‐2 quad‐polarization SAR image[J]. Geophysical Research Letters, 2011, 38(10): L10602.
[13]	Li Chenglei, Kim D J, Park S, et al. A self-evolving deep learning algorithm for automatic oil spill detection in Sentinel-1 SAR images[J]. Remote Sensing of Environment, 2023, 299: 113872. doi: 10.1016/j.rse.2023.113872
[14]	Salisbury J W, D'Aria D M, Sabins Jr F F. Thermal infrared remote sensing of crude oil slicks[J]. Remote Sensing of Environment, 1993, 45(2): 225−231. doi: 10.1016/0034-4257(93)90044-X
[15]	Tseng W Y, Chiu L S. AVHRR observations of Persian Gulf oil spills[C]//Proceedings of IGARSS'94-1994 IEEE International Geoscience and Remote Sensing Symposium. Pasadena: IEEE, 1994: 779−782.
[16]	Svejkovsky J, Lehr W, Muskat J, et al. Operational utilization of aerial multispectral remote sensing during oil spill response[J]. Photogrammetric Engineering & Remote Sensing, 2012, 78(10): 1089−1102.
[17]	Shih W C, Andrews A B. Modeling of thickness dependent infrared radiance contrast of native and crude oil covered water surfaces[J]. Optics Express, 2008, 16(14): 10535−10542. doi: 10.1364/OE.16.010535
[18]	Lu Yingcheng, Zhan Wenfeng, Hu Chuanmin. Detecting and quantifying oil slick thickness by thermal remote sensing: a ground-based experiment[J]. Remote Sensing of Environment, 2016, 181: 207−217. doi: 10.1016/j.rse.2016.04.007
[19]	Jiao Junnan, Lu Yingcheng, Hu Chuanmin, et al. Quantifying ocean surface oil thickness using thermal remote sensing[J]. Remote Sensing of Environment, 2021, 261: 112513. doi: 10.1016/j.rse.2021.112513
[20]	刘建强. 全球海面油膜遥感[J]. 科学通报, 2022, 67(33): 3897−3899. doi: 10.1360/TB-2022-0692 Liu Jianqiang. Remote sensing of oil slicks in global oceans[J]. Chinese Science Bulletin, 2022, 67(33): 3897−3899. doi: 10.1360/TB-2022-0692
[21]	刘建强, 陆应诚, 丁静, 等. 中国海洋水色业务卫星揭示我国近海溢油污染状况[J]. 科学通报, 2022, 67(33): 3997−4008. doi: 10.1360/TB-2021-0992 Liu Jianqiang, Lu Yingcheng, Ding Jing, et al. Oil spills in China Seas revealed by the national ocean color satellites[J]. Chinese Science Bulletin, 2022, 67(33): 3997−4008. doi: 10.1360/TB-2021-0992
[22]	Sun Shaojie, Lu Yingcheng, Liu Yongxue, et al. Tracking an oil tanker collision and spilled oils in the East China Sea using multisensor day and night satellite imagery[J]. Geophysical Research Letters, 2018, 45(7): 3212−3220. doi: 10.1002/2018GL077433
[23]	陆应诚, 刘建强, 丁静, 等. 中国东海“桑吉”轮溢油污染类型的光学遥感识别[J]. 科学通报, 2019, 64(31): 3213−3222. Lu Yingcheng, Liu Jianqiang, Ding Jing, et al. Optical remote identification of spilled oils from the SANCHI oil tanker collision in the East China Sea[J]. Chinese Science Bulletin, 2019, 64(31): 3213−3222.
[24]	Zhu Xiaobo, Lu Yingcheng, Liu Jianqiang, et al. Optical extraction of oil spills from satellite images under different sunglint reflections[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 4210714.
[25]	Lu Yingcheng, Shi Jing, Wen Yansha, et al. Optical interpretation of oil emulsions in the ocean–Part I: laboratory measurements and proof-of-concept with AVIRIS observations[J]. Remote Sensing of Environment, 2019, 230: 111183. doi: 10.1016/j.rse.2019.05.002
[26]	Lu Yingcheng, Shi Jing, Hu Chuanmin, et al. Optical interpretation of oil emulsions in the ocean–Part II: applications to multi-band coarse-resolution imagery[J]. Remote Sensing of Environment, 2020, 242: 111778. doi: 10.1016/j.rse.2020.111778
[27]	Hu Chuanmin, Lu Yingcheng, Sun Shaojie, et al. Optical remote sensing of oil spills in the ocean: what is really possible?[J]. Journal of Remote Sensing, 2021, 9141902. (查阅网上资料, 未找到本条文献卷, 期信息, 请确认)
[28]	Jiao Junnan, Lu Yingcheng, Hu Chuanmin. Optical interpretation of oil emulsions in the ocean-Part III: a three-dimensional unmixing model to quantify oil concentration[J]. Remote Sensing of Environment, 2023, 296: 113719. doi: 10.1016/j.rse.2023.113719
[29]	Lu Yingcheng, Zhou Yang, Liu Yongxue, et al. Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle[J]. Journal of Geophysical Research: Oceans, 2017, 122(8): 6342−6354. doi: 10.1002/2017JC012793
[30]	Hu Chuanmin, Li Xiaofeng, Pichel W G, et al. Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery[J]. Geophysical Research Letters, 2009, 36(1): L01604.
[31]	Jackson C R, Alpers W. The role of the critical angle in brightness reversals on sunglint images of the sea surface[J]. Journal of Geophysical Research: Oceans, 2010, 115(C9): C09019.
[32]	Wettle M, Daniel P J, Logan G A, et al. Assessing the effect of hydrocarbon oil type and thickness on a remote sensing signal: a sensitivity study based on the optical properties of two different oil types and the HYMAP and Quickbird sensors[J]. Remote Sensing of Environment, 2009, 113(9): 2000−2010. doi: 10.1016/j.rse.2009.05.010
[33]	Kukhtarev N, Kukhtareva T, Gallegos S C. Holographic interferometry of oil films and droplets in water with a single-beam mirror-type scheme[J]. Applied Optics, 2011, 50(7): B53−B57. doi: 10.1364/AO.50.000B53
[34]	Zhou Yang, Lu Yingcheng, Shen Yafeng, et al. Polarized remote inversion of the refractive index of marine spilled oil from PARASOL images under sunglint[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2710−2719. doi: 10.1109/TGRS.2019.2953640
[35]	Lu Yingcheng, Li Xiang, Tian Qingjiu, et al. Progress in marine oil spill optical remote sensing: detected targets, spectral response characteristics, and theories[J]. Marine Geodesy, 2013, 36(3): 334−346. doi: 10.1080/01490419.2013.793633
[36]	Clark R N, Swayze G A, Leifer I, et al. A method for quantitative mapping of thick oil spills using imaging spectroscopy[R]. Denver: U. S. Geological Survey, 2010.
[37]	Kirillov A, Mintun E, Ravi N, et al. Segment anything[C]//Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision. Paris: IEEE, 2023: 3992−4003.
[38]	Ma Jun, He Yuting, Li Feifei, et al. Segment anything in medical images[J]. Nature Communications, 2024, 15(1): 654. doi: 10.1038/s41467-024-44824-z
[39]	Agreement B. Bonn agreement aerial operations handbook, 2016[R]. London: Bonn Agreement, 2016. (查阅网上资料, 未找到本条文献出版信息、不确定作者信息, 请确认)