Calculation Method of Oil Slick Area on Sea Surface Using High-resolution Satellite Imagery: M/V Symphony Oil Spill Accident |
Kim, Tae-Ho
(Department of Remote Sensing, Underwater Survey Technology 21 Corp.)
Shin, Hye-Kyeong (Department of Remote Sensing, Underwater Survey Technology 21 Corp.) Jang, So Yeong (Department of Remote Sensing, Underwater Survey Technology 21 Corp.) Ryu, Joung-Mi (Department of Remote Sensing, Underwater Survey Technology 21 Corp.) Kim, Pyeongjoong (Oceanic Research Division, Underwater Survey Technology 21 Corp.) Yang, Chan-Su (Marine Security and Safety Research Center, Korea Institute of Ocean Science and Technology) |
1 | Arslan, N., 2018. Assessment of oil spills using Sentinel 1 C-band SAR and Landsat 8 multispectral sensors, Environmental Monitoring and Assessment, 190(11): 637. DOI |
2 | Bayramov, E., M. Kada, and M. Buchroithner, 2018. Monitoring oil spill hotspots, contamination probability modelling and assessment of coastal impacts in the Caspian Sea using SENTINEL1, LANDSAT-8, RADARSAT, ENVISAT and ERS satellite sensors, Journal of Operational Oceanography, 11(1): 27-43. DOI |
3 | ESA Copernicus Open Access Hub (European Space Agency Copernicus Open Access Hub), https://scihub.copernicus.eu/dhus/#/home, Accessed on Apr. 27-May. 13, 2021. |
4 | Garcia-Pineda, O., G. Staples, C.E. Jones, C. Hu, B. Holt, V. Kourafalou, G. Graettinger, L. DiPinto, E. Ramirez, D. Streett, J. Cho, G.A. Swayze, S. Sun, D. Garcia, and F. Haces-Garcia, 2020. Classification of oil spill by thickness using multiple remote sensors, Remote Sensing of Environment, 236: 111421. DOI |
5 | Kim, D. and H.-S. Jung, 2018. Mapping oil spills from dual-polarized SAR images using an Artificial Neural Network: Application to oil spill in the Kerch Strait in November 2007, Sensors, 18(7): 2237. DOI |
6 | Kim, Y. and K.-N. Kang, 2021. A study on the utilization of SAR microsatellite constellation for ship detection, Korean Journal of Remote Sensing, 37(3): 627-363 (in Korean with English abstract). DOI |
7 | Lee, S., 2017. Image Restoration and Segmentation for PAN-sharpened High Multispectral Imagery, Korean Journal of Remote Sensing, 33(6-1): 1003-1017 (in Korean with English abstract). DOI |
8 | Mityagina, M. and O. Lavrova, 2016. Satellite Survey of Inner Seas: Oil Pollution in the Black and Caspian Seas, Remote Sensing, 8(10): 875. DOI |
9 | Bianchi, M.F., M.M. Espeseth, and N. Borch, 2020. Large-Scale detection and categorization of oil spills from SAR image with Deep Learning, Remote Sensing, 12: 2260. DOI |
10 | Alpers, W., B. Holt, and K. Zeng, 2017. Oil spill detection by imaging radars: Challenges and pitfalls, Remote Sensing of Environment, 201: 1522-1525. |
11 | Zhang, J., H. Feng, Q. Luo, Y. Li, J. Wei, and J. Li, 2020. Oil spill detection in Quad-Polarimetric SAR images using an Advanced Convolutional Neural Network based on SuperPixel Model, Remote Sensing, 12: 944. DOI |
12 | Krestenitis, M., G. Orfanidis, K. Ioannidis, K. Avgerinakis, S. Vrochidis, and I. Kompatsiaris, 2019. Oil spill identification from satellite images using Deep Neural Networks, Remote Sensing, 11: 1762 DOI |
13 | Park, S.-H., H.-S. Jung, and M.-J. Lee, 2020. Oil spill mapping from Kompsat-2 high-resolution image using Directional Median Filtering and Artificial Neural Network, Remote Sensing, 12(2): 253. DOI |
14 | Xing, Q., L. Li, M. Lou, L. Bing, R. Zhao, and Z. Li, 2015. Observation of Oil Spills through Landsat Thermal Infrared Imagery: A Case of Deepwater Horizon, Aquatic Procedia, 3: 151-156. DOI |
15 | Zhao, J., M. Temimi, H. Ghedira, and C. Hu, 2014. Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf, Optics Express, 22(11): 13755-13772. DOI |
16 | Park, S.-H., H.-S. Jung, M.-J Lee, W.-J. Lee, and M.-J. Choi, 2019. Oil Spill Detection from PlanetScope Satellite Image: Application to Oil Spill Accident near Ras AI Zour Area, Kuwait in August 2017, Journal of Coastal Research, 90: 251-260. DOI |
17 | Park, S., M.-H. Ahn, C. Li, J. Kim, H. Jeon, and D.-J. Kim, 2021. Evaluation of oil spill detection models by oil spill distribution characteristics and CNN architectures using Sentinel-1 SAR data, Korean Journal of Remote Sensing, 37(5-3): 1475-1490 (in Korean with English abstract). DOI |
18 | Robbe, N. and T. Hengstermann, 2006. Remote sensing of marine oil spills from airborne platforms using multi-sensor systems, Water Pollution VIII: Modelling, Monitoring and Management, 1: 347-355. |
19 | Ira, L., J.L. William, S. Debra, B. Eliza, C. Roger, D. Philip, H. Yongxiang, M. Scott, E.J. Cathleen, H. Benjamin, R. Molly, A.R. Dar, S. Jan, S. Gregg, W. Jennifer, 2012. State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill, Remote Sensing of Environment, 124(2012): 185-209. DOI |
20 | Solberg, A.H.S., 2012. Remote sensing of ocean oilspill pollution, Proceedings of the IEEE, 100(10): 2931-2945. DOI |
21 | Putra, M.I.J., M.M. Anugerah, and A. Akbar, 2019. Sentinel 1 (SAR) and Sentinel 2 (MSI) Imagery Capabilites for Oil Spill Detection in Balikpapan Bay, Seminar Nasional Penginderaan Jauh, Proc. of Seminar Nasional Penginderaan Jauh ke-6 Tahun 2019, Depok, INA, Jul. 17, pp. 321-327. |
22 | Zeng, K. and Y. Wang, 2020. A Deep Convolutional Neural Network for Oil Spill Detection from Spaceborne SAR Images, Remote Sensing, 12: 1015. DOI |
23 | Rajendran, S., P. Vethamony, F.N. Sadooni, H.A.-S. AlKuwari, J.A. Al-Khayat, V.O. Seegobin, H. Govil, and S. Nasir, 2021. Detection of Wakashio oil spill off Mauritius using Sentinel-1 and 2 data: Capability of sensors, image transformation methods and mapping, Environmental Pollution, 274: 116618. DOI |