Progress in Research on Marine Oil Spills Detection Using Synthetic Aperture Radar
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摘要:
海洋溢油污染不仅严重威胁海洋生态安全、破坏海岸带环境，而且直接和间接地影响着广大人民群众的生活和健康以及区域社会经济的发展。合成孔径雷达因其具有全天候和高灵敏度的观测能力而成为海面油膜探测的主要手段之一。该文从SAR海面油膜探测的基本原理出发，介绍了单极化、全极化和紧缩极化SAR海面油膜探测技术的国内外最新研究进展，对该技术手段在实际应用中遇到的主要困难和挑战做了深入分析，最后总结展望了该技术未来发展的广阔前景。
Abstract:Marine oil spill pollution is a serious threat to the marine ecological environment, human life and economic development. Synthetic Aperture Radar (SAR) becomes one of the main technologies for marine oil film detection because of its all-weather and high sensitivity observation capability. This article first introduces the research progress of oil film detection technology on single polarimetric, fully polarimetric and compact polarimetric SAR technologies, based on the basic principle of SAR oil slick detection. Then the main difficulties and challenges encountered in the current research are analyzed. Finally, the broad prospects for the future development of this technology are forecasted.
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Key words:
- Synthetic Aperture Radar (SAR) /
- Polarimetry /
- Oil spill /
- Classification
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表 1 常用单极化SAR油膜特征
强度特征 形态学特征 纹理特征* 环境特征 油膜后向散射强度(${\mu _{{\rm{obj}}}}$) 面积(A) 同质性(Homogeneity) 距海岸距离 油膜后向散射方差(${\sigma _{{\rm{obj}}}}$) 周长(P ) 对比度(Contrast) 距最近黑斑距离 油膜周围后向散射(${\mu _{{\rm{sce}}}}$) 复杂度(C ) 差异度(Dissimilarity) 周围黑斑数量 灰度比(${\mu _{{\rm{obj}}}}/{\mu _{{\rm{sce}}}}$) 不对称性 熵(Entropy) 周围船只数量 方差比(${\sigma _{{\rm{obj}}}}/{\sigma _{{\rm{sce}}}}$) 欧拉数 均值(Mean) … ISRI(${\mu _{{\rm{obj}}}}/{\sigma _{{\rm{obj}}}}$) 形状指数 方差(Variance) ISRO(${\mu _{{\rm{obj}}}}/{\sigma _{{\rm{sce}}}}$) 轴线长度 相关性(Correlation) 油膜最小灰度值(MSV) 紧致度 最大对比度(${\sigma _{{\rm{sce}}}}$-MSV) 边缘梯度 注：纹理特征通过灰度共生矩阵(Gray-Level Co-occurrence Matrix, GLCM)得到 
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刘鹏. SAR海面溢油检测与识别方法研究[D]. [博士论文], 中国海洋大学, 2012.LIU Peng. Research on ocean oil spill detection and recognition[D]. [Ph.D. dissertation], Ocean University of China, 2012: 1–2. 朱姝霖. 海上溢油事故的影响及处理分析[J]. 航海, 2011(4): 54–56.ZHU Shulin. The influence and treatment analysis of the marine oil spill accident[J]. Navigation, 2011(4): 54–56. Deepwater Horizon oil spill[OL]. https://en.wikipedia.org/wiki/Deepwater_Horizon_oil_spill. 罗孝学, 许庭春. 海上溢油事故及其防范[J]. 中国水运: 理论版, 2006, 4(7): 18–19.LUO Xiaoxue and XU Tingchun. Marine oil spill accident at sea and its prevention[J]. China Water Transport, 2006, 4(7): 18–19. 劳辉. 最近29年我国沿海船舶、码头溢油50吨以上事故统计[J]. 交通环保, 2003, 24(6): 47.LAO Hui. Statistics on accidents of over 50 tons of oil spills on ships and wharfs along the coast in recent 29 years[J]. Environmental Protection in Transportation, 2003, 24(6): 47. NOAA. NOAA office of response and restoration, open water oil identification job aid for aerial observation. [OL]. http://response.restoration.noaa.gov/jobaid/orderform, 2016. SUKAWATTANAVIJIT C, CHEN Jie, and ZHANG Hongsheng. GA-SVM algorithm for improving land-cover classification using SAR and optical remote sensing data[J]. IEEE Geoscience & Remote Sensing Letters, 2017, 14(3): 284–288. doi: 10.1109/LGRS.2016.2628406 LIU Lin and ZHANG Yuanzhi. Urban heat island analysis using the landsat TM data and ASTER data: A case study in Hong Kong[J]. Remote Sensing, 2011, 3(7): 1535–1552. doi: 10.3390/rs3071535 ZHANG Yuanzhi, PULLIAINEN J, KOPONEN S, et al. Application of an empirical neural network to surface water quality estimation in the Gulf of Finland using combined optical data and microwave data[J]. Remote Sensing of Environment, 2002, 81(2): 327–336. doi: 10.1016/S0034-4257(02)00009-3 Jones C , Holt B. Experimental L-Band Airborne SAR for Oil Spill Response at Sea and in Coastal Waters[J]. Sensors, 2018, 18(2): 641–106. doi: 10.3390/s18020641 GAUTHIER M, WEIR L, OU Z, et al. Integrated satellite tracking of pollution: A new operational program[C]. IEEE International Geoscience & Remote Sensing Symposium, Barcelona, Spain, 2007: 967–970. 刘康炜, 杨文玉. 海上溢油监测技术研究进展[J]. 安全、健康和环境, 2012, 12(7): 1–3. doi: 10.3969/j.issn.1672-7932.2012.07.002 CHEN Jie, IQBAL M, YANG Wei, et al. Mitigation of azimuth ambiguities in spaceborne stripmap SAR images using selective restoration[J]. IEEE Transactions on Geoscience & Remote Sensing, 2014, 52(7): 4038–4045. doi: 10.1109/TGRS.2013.2279109 BAMLER R. Principles of synthetic aperture radar[J]. Surveys in Geophysics, 2001, 21(2-3): 147–157. doi: 10.1023/A:1006790026612 ARISTOTLE. Problematica Physica[M].Leiden, Koninklijke Brill NV, 2015. MARANGONI C. Sul principio della viscosita superficiale dei liquidi stabili[J]. Nuovo Cimento, 1872, 5-6(1): 239–273. doi: 10.1007/BF02718643 SOLBERG A H S. Remote sensing of ocean oil-spill pollution[J]. Proceedings of the IEEE, 2012, 100(10): 2931–2945. doi: 10.1109/JPROC.2012.2196250 SOLBERG AHS, STORVIK G, SOLBERG R, et al. Automatic detection of oil spills in ERS SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(4): 1916–1924. doi: 10.1109/36.774704 MIGLIACCIO M, FERRARA G, GAMBARDELLA A, et al. A new stochastic model for oil spill observation by means of single-look SAR data[J]. Environmental Research, Engineering and Management, 2007, 1(39): 24–29. doi: 10.1109/BALTIC.2006.7266181 SHU Yuanming, LI J, and YOUSIF H. Dark-spot detection from SAR intensity imagery with spatial density thresholding for oil-spill monitoring[J]. Remote Sensing of Environment, 2010, 114(9): 2026–2035. doi: 10.1016/j.rse.2010.04.009 BARNI M, BETTI M, and MECOCCI A. A fuzzy approach to oil spill detection on SAR images[J]. IEEE International Geoscience and Remote Sensing Symposium, 1995, 1(I): 157–159. doi: 10.1109/IGARSS.1995.519676 MERCIER G, DERRODE S, PIECZYNSKI W, et al. Multiscale oil slick segmentation with Markov Chain Model[C]. IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 2003: 3501–3503. HUANG Bo, LI Hongga, and HUANG X. A level set method for oil slick segmentation in SAR images[J]. International Journal of Remote Sensing, 2005, 26(6): 1145–1156. doi: 10.1080/01431160512331326747 ZHANG Yuanzhi, LIN Hui, LIU Qiang, et al. Oil-spill monitoring in the coastal waters of Hong Kong and vicinity[J]. Marine Geodesy, 2012, 35(1): 93–106. doi: 10.1080/01490419.2011.637872 SOLBERG A, DOKKEN S T and SOLBERG R, Automatic detection of oil spills in ENVISAT, Radarsat and ERS SAR images[C]. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings, Toulouse, 2003, 4: 2747–2749. FISCELLA B, GIANCASPRO A, NIRCHIO F, et al. Oil spill detection using marine SAR images[J]. International Journal of Remote Sensing, 2000, 21(18): 3561–3566. doi: 10.1080/014311600750037589 DEL FRATE F, PETROCCHI A, LICHTENEGGER J, et al. Neural networks for oil spill detection using ERS-SAR data[J]. IEEE transactions on geoscience and remote sensing, 2000, 38(5): 2282–2287. doi: 10.1109/IGARSS.1999.773451 TOPOUZELIS K, KARATHANASSI V, PAVLAKIS P, et al. Detection and discrimination between oil spills and look-alike phenomena through neural networks[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2007, 62(4): 264–270. doi: 10.1016/j.isprsjprs.2007.05.003 NIRCHIO F, SORGENTE M, GIANCASPRO A, et al. Automatic detection of oil spills from SAR images[J]. International Journal of Remote Sensing, 2005, 26(6): 1157–1174. doi: 10.1080/01431160512331326558 KERAMITSOGLOUA I, CARTALISA C, and KIRANOUDIS C. Automatic identification of oil spills on satellite images[J]. Environmental Modeling & Software, 2006, 21(5): 640–652. doi: 10.1016/j.envsoft.2004.11.010 GAMBARDELLA A, GIACINTO G, and MIGLIACCIO M. On the mathematical formulation of the SAR oil-spill observation problem[C], IEEE International Geoscience and Remote Sensing Symposium, Boston, USA, 2008: 1382–1385. MARGHANY M, CRACKNELL A, and HASHIM M. Modification of fractal algorithm for oil spill detection from RADARSAT-1 SAR data[J]. International Journal of Applied Earth Observation and Geoinformation, 2009, 11(2): 96–102. doi: 10.1016/j.jag.2008.09.002 GARCIA-PINEDA O, MACDONALD I R, LI Xiaofeng, et al. Oil spill mapping and measurement in the gulf of mexico with textural classifier neural network algorithm (TCNNA)[J]. Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(6): 2517–2525. doi: 10.1109/JSTARS.2013.2244061 MARGHANY M. Genetic algorithm for oil spill automatic detection from Envisat satellite data[C]. Computational Science and Its Applications - ICCSA, Ho Chi Minh City, Vietnam, 2013: 587–598. BROWN C E, and FINGAS M F. Synthetic Aperture Radar sensors: viable for marine oil spill response[C]. Arctic and Marine Oil spill Program, Canada, 2003: 299–310. MIGLIACCIO M, GAMBARDELLA A, and TRANFAGLIA M. SAR polarimetry to observe oil spills[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(2): 506–511. doi: 10.1109/TGRS.2006.888097 MIGLIACCIO M, and TRANFAGLIA M. Study on the use of SAR polarimetric data to observe oil spills[C]. Europe Oceans 2005, Brest, France, 2005: 196–200. MIGLIACCIO M, FERRARA G, GAMBARDELLA A, et al. A new stochastic model for oil spill observation by means of single-look SAR data[J]. Environmental Engineering and Management Journal, 2007, 1(39): 24–29. doi: 10.1109/BALTIC.2006.7266181 NUNZIATA F, MIGLIACCIO M, and GAMBARDELLA A. Pedestal height for sea oil slick observation[J]. Radar, Sonar & Navigation, 2011, 5(2): 103–110. doi: 10.1049/iet-rsn.2010.0092 MIGLIACCIO M, NUNZIATA F, and GAMBARDELLA A. On the copolarized phase difference for oil spill observation[J]. International Journal of Remote Sensing, 2009, 30(6): 1587–1602. doi: 10.1080/01431160802520741 SKRUNES S, BREKKE C, and ELTOFT T. An experimental study on oil spill characterization by multi-polarization SAR[C]. 9th European Conference on Synthetic Aperture Radar, Nuremberg, Germany, 2012: 139–142. MELSHELMER C, ALPERS W, and GADE M. Investigation of multifrequency/multipolarization radar signatures of rain cells, derived from SIR-C/X-SAR data[C]. Geoscience and Remote Sensing Symposium, Lincoln, USA 1996: 1370–1372. MINCHEW B, JONES C E, and HOLT B. Polarimetric analysis of backscatter from the deepwater Horizon oil spill using L-Band synthetic aperture radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(10): 3812–3830. doi: 10.1109/TGRS.2012.2185804 NUNZIATA F, SOBIESKI P, and MIGLIACCIO M. The Two-Scale BPM scattering model for sea biogenic slicks contrast[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(7): 1949–1956. doi: 10.1109/TGRS.2009.2013135 田维. 海面油膜雷达遥感检测机理与方法研究[D]. [博士论文], 中国科学院遥感应用研究所, 2009. LI Yu, ZHANG Yuanzhi, CHEN Jie, et al. Model-based sea surface scattering analysis for the DWH oil spill accident case[C]. Geoscience and Remote Sensing Symposium, Beijing, China, 2016: 7711–7714. HANJSEK I, POTTIER E, and CLOUDE S R. Inversion of surface parameters from polarimetric SAR[J]. Geoscience and Remote Sensing, IEEE Transactions on, 2003, 41(4): 727–744. doi: 10.1109/TGRS.2003.810702 WANG Wenguang, LU Fei, WU Peng, et al. Oil spill detection from polarimetric SAR image[J]. Proc. Int. Conf. Signal Process, 2010: 832–835. doi: 10.1109/ICOSP.2010.5655943 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): 415–421. doi: 10.1029/2011GL047013 SKRUNES S, BREKKE C, JONES C E, et al. A multisensor comparison of experimental oil spills in polarimetric SAR for high wind conditions[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2016, 9(11): 4948–4961. doi: 10.1109/JSTARS.2016.2565063 CHEN Jie and QUEGAN S. Calibration of spaceborne CTLR compact polarimetric low-frequency SAR using mixed radar calibrators[J]. IEEE Transactions on Geoscience & Remote Sensing, 2011, 49(7): 2712–2723. doi: 10.1109/TGRS.2011.2109065 RANEY R K. Hybrid-Polarity SAR architecture[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(11): 3397–3404. doi: 10.1109/TGRS.2007.895883 AINSWORTH T L, KELLY J P, and LEE J S. Classification comparisons between dual-pol, compact polarimetric and quad-pol SAR imagery[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2009, 64(5): 464–471. doi: 10.1016/j.isprsjprs.2008.12.008 LAVALLE M, POTTIER E, SOLIMINI D, et al. Compact polarimetric SAR Interferometry: PALSAR observations and associated reconstruction algorithms[C]. Workshop on Science and Applications of SAR Polarimetry and Polarimetric, Frascati, Italy, 2009: 26–30. SOUYRIS JC, STACY N, AINSWORTH T, et al. SAR Compact Polarimetry (CP) for earth observation and planetology: Concept and challenges[C]. Proceedings of International Workshop on Science & Applications of Sar Polarimetry & Polarimetric Interferometry, Noordwijk, Netherlands, 2007: 22–26. NORD M E, AINSWORTH T L, et al. Comparison of compact polarimetric synthetic aperture radar modes[J]. IEEE Transactions on Geoscience & Remote Sensing, 2009, 47(1): 174–188. doi: 10.1109/TGRS.2008.20009 YIN Junjun, YANG Jian, and ZHANG Xinzheng. On the ship detection performance with compact polarimetry[C]. IEEE Radar Conference, Kansas City, USA, 2011: 675–680. COLLINS M J, DENBINA M, and ATTEIA G. On the reconstruction of Quad-Pol SAR data from compact polarimetry data for ocean target detection[J]. IEEE Transactions on Geoscience & Remote Sensing, 2012, 51(1): 591–600. doi: 10.1109/TGRS.2012.2199760 ZHANG Biao, LI Xiaofeng, PERRIE W, et al. Compact polarimetric synthetic aperture radar for marine oil platform and slick detection[J]. IEEE Transactions on Geoscience & Remote Sensing, 2017, 55(3): 1407–1423. doi: 10.1109/TGRS.2016.2623809 LI Yu, ZHANG Yuanzhi, CHEN Jie, et al. Improved compact polarimetric SAR Quad-Pol reconstruction algorithm for oil spill detection[J]. IEEE Geoscience & Remote Sensing Letters, 2014, 11(6): 1139–1142. doi: 10.1109/LGRS.2013.2288336 SHIRVANY R, CHABERT M, and TOURNERET J Y. Ship and oil-spill detection using the degree of polarization in linear and hybrid/compact Dual-Pol SAR[J]. Selected Topics in Applied Earth Observations and Remote Sensing, 2012, 5(3): 885–892. doi: 10.1109/JSTARS.2012.2182760 CLOUDE S R, GOODENOUGH D G, and CHEN H. Compact decomposition theory[J]. Geoscience and Remote Sensing Letters, 2011, 9(1): 28–32. doi: 10.1109/LGRS.2011.2158983 LI Haiyan, PERRIE W, HE Yijun, et al. Target detection on the ocean with the relative phase of compact polarimetry SAR[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013, 51(6): 3299–3305. doi: 10.1109/TGRS.2012.2224119 LI Haiyan, PERRIE W, HE Yijun, et al. Analysis of the polarimetric SAR scattering properties of oil-covered waters[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2015, 8(8): 3751–3759. doi: 10.1109/JSTARS.2014.2348173 TRUONG-LOI M, DUBOIS-FERNANDEZ P, FREEMAN A and POTTIER E, The conformity coefficient or how to explore the scattering behaviour from compact polarimetry mode[C]. 2009 IEEE Radar Conference, Pasadena, CA, 2009: 1-6. YIN Junjun, YANG Jian, ZHOU ZhengShu, et al. The extended Bragg scattering model-based method for ship and oil-spill observation using compact polarimetric SAR[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2015, 8(8): 3760–3772. doi: 10.1109/JSTARS.2014.2359141 NUNZIATA F, MIGLIACCIO M, and LI Xiaofeng. Sea oil slick observation using Hybrid-Polarity SAR architecture[J]. IEEE Journal of Oceanic Engineering, 2015, 40(2): 426–440. doi: 10.1109/JOE.2014.2329424 LI Yu, LIN Hui, ZHANG Yuanzhi, et al. Comparisons of circular transmit and linear receive compact polarimetric SAR features for oil slicks discrimination[J]. Journal of Sensors, 2015, 2015(99): 1–14. doi: 10.1155/2015/631561 ZHANG Yuanzhi, LI Yu, LIANG X, et al. Comparison of oil spill classifications using fully and compact polarimetric SAR images[J]. Applied Sciences, 2017, 7(2): 193. doi: 10.3390/app7020193 KUMAR L J V, KISHORE J K, and RAO P K. Decomposition methods for detection of oil spills based on Risat-1 SAR images[J]. Remote Sens. Geosci, 2014, 3(4): 1–10. BUONO A, NUNZIATA F, MIGLIACCIO M, et al. Polarimetric analysis of compact-polarimetry SAR architectures for sea oil slick observation[J]. IEEE Transactions on Geoscience & Remote Sensing, 2016, 54(10): 5862–5874. doi: 10.1109/TGRS.2016.2574561 ALPERS W, HOLT B, and ZENG K. Oil spill detection by imaging radars: Challenges and pitfalls[J]. In Remote Sensing of Environment, 2017, 201(2017): 133–147. doi: 10.1016/j.rse.2017.09.002 CHEN Jie and QUEGAN S. Improved estimators of faraday rotation in spaceborne polarimetric SAR data[J]. IEEE Geoscience & Remote Sensing Letters, 2010, 7(4): 846–850. doi: 10.1109/LGRS.2010.2047002 R A N E Y R , H y b r i d - P o l a r i t y S A R A r c h i t e c t u r e [ C ] . 2 0 0 6 I E E E I n t e r n a t i o n a l S y m p o s i u m o n G e o s c i e n c e a n d R e m o t e S e n s i n g , D e n v e r , C O , 2 0 0 6 : 3 8 4 6 - 3 8 4 8 . d o i : CHEN Guandong, LI Yu, SUN Guangmin, et al. Application of deep networks to oil spill detection using polarimetric Synthetic Aperture Radar Images[J]. Applied Sciences, 2017, 7(10): 968. doi: 10.3390/app7100968 -
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