he advantages of quad-polarization. Generally speaking, the sys-tematic analysis of the influence of observing condition, environ-ment parameters and the noise level on the polarization para-meters has not been done for oil spill identification. Meanwhile,the simultaneous consideration of observing conditions, envir-onment parameters and image noises has not been carried outfor pol SAR oil spill detection.The paper collects Radarsat–2 polarization data of differentincidences, wind speeds, noise levels and surface phenomena(oil and look likes) to analyze the impacts of the observing condi-tions, the environment parameters and the noise levels on thepolarization parameters of the oil spill detection. The paper con-cludes the following sections. Section 1 is a brief introduction.Section 2 describes the data used in the paper. Section 3 intro-duces three polarimetric parameters, and Section 4 makes theanalysis of the three parameters and the influence of the ob-serving conditions, the environmental parameters and the imagenoises on the polarization parameters. The verification is also in-cluded. Finally, a conclusion is given in Section 5.2  SAR dataEight Radarsat–2 images of the China offshore, the Gulf ofMexico and the North Sea from 2008 to 2012 have been used. Thephenomena in SAR images include oil slick, low wind area andbiogenic slicks. The images cover incidence 29°–50°, NESZ –31 to–36 d B, and wind speed 1.6–9.0 m/s, as shown in Table 1. The in-cidence angle and the NESZ are acquired from head file, wherethe incidence increases with the beam number, and the NESZ in-creases with incidence. The wind speed is obtained from literat-ure and NCEP forecast wind. Two typical SAR images are used inSection 4.1 to investigate the three polarimetric parameters men-tioned in Section 3, and all of the eight images are used in Sec-tion 4.1 to analyze the influence of the observing conditions, theenvironmental parameters and the image noises on the polariza-tion parameters.3  Polarimetric parametersThe paper lays emphasis on the polarization SAR parametersrepresenting the relative magnitudes of co-polarization andcross-polarization powers, including the conformity coefficient(μ), the Muller parameters (|C|, B0) and the eigenvalues (λnos) ofthe simplified coherency matrix.3.1  Conformity coefficientThe concept of the conformity coefficient originates from theinversion of soil moisture from compact polarimetry data (Dubois-Fernandez et al., 2008). The parameter can discriminate surfacescattering, double-bounce scattering and volume scattering. Theconformity coefficient is expressed as¹¼2 h Re(SHHS ¤VV)¡ jSHVj2i³j SHHj2+ 2jSHVj2+jSVVj2´; (1) where SHH, SHV and SVV are the complex amplitudes of the scat-tering matrix, subscripts H and V represents remitting and re-ceiving polarization.For land surfaces, SHV is small, SHH and SVV are relevant,phase difference is close to 0, so conformity coefficient is positive,t1<μ<1, where t1 is a threshold value larger than 0.For double-bounce scattering targets, SHH and SVV are relev-ant, phase difference is close to 180°, so conformity coefficient isnegative, –1<μ<t2, where t2 is threshold value below 0.For volume scattering, SHH and SVV are weakly correlated, SHVis large, so t1<μ<t2, t1, t2 are determined by statistics.When the sea surface is well modeled by Bragg scattering(Schuler et al., 1993; Zhang et al., 2011), SHV is small, close to 0,and SHH and SVV are highly correlated with phase difference closeto 0, so μ>0; when it is non-Bragg scattering, vessels for example,SHH and SVV are weakly correlated with phase difference close to180°, so μ<0.3.2  Muller parametersMuller matrix gives the relationship between an incidentStokes vector and a reflecting Stokes vector (Van Zyl et al., 1987;Guissard, 1994), which could be expressed by a 4×4 matrix:¿*gsÀ =hMi*gi; (2) *gi*gswhere  and  are the incident Stokes vector and the reflectingStokes vector, respectively.For the sea surface, there are only eight non-zero elements inthe Muller matrix, considering the low correlation between co-and cross-polarization (Cloud, 1985; Van Zyl, 1989; Nghiem et al.,1992; Ulaby et al., 1992),M =0BB@A + B0B 0 0B A¡B00 00 0 C + B0D0 0¡D C¡B01CCA; (3) whereA =12Dj SHHj2+jSVVj2E; (4) B =12Dj SHHj2¡ jSVVj2E; (5) Table 1.   Polarization SAR dataNo. UTC time Location Mode NESZ/d B Incidence/(°) Wind speed/m·s–1 Dark phenomena1 2010–05–15 11:56 28.5°N,   88.3°W FQ10 –33.3 to –35.6 29.2–30.9 9.0 oil slick2 2011–06–08 17:27 60.0°N,      2.3°E   FQ15 –33.0 to –35.0 34.5–36.1 1.6–3.3 oil slick3 2008–07–13 10:49 18.2°N, 109.8°E FQ15 –33.1 to –35.8 34.4–36.0 2.0–3.0 low wind area4 2012–08–18 22:12 20.7°N, 116.7°E FQ10 –33.1 to –35.7 29.2–30.9 2.0–2.3 low wind area5 2011–05–16 10:09 38.3°N, 118.8°E FQ25 –31.5 to –32.8 43.6–44.9 2.0–3.0 low wind area6 2010–05–08 12:01 26.8°N,   92.0°W   FQ23 –32.0 to –33.0 41.9–43.3 6.5 oil slick7 2012–08–13 22:57 20.7°N, 116.6°E FQ31 –31.3 to –32.1 48.3–49.5 3.0–5.0 biogenic slick8 2008–08–23 10:53 18.2°N, 109.6°E FQ21 –32.1 to –34.2 40.1–41.6 3.0 low wind area78 SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87  B0=Dj SHVj2E; (6) C =h<(SHHS ¤VV)i; (7) D =h=(SHHS ¤VV)i: (8) |C| is related to SHH and SVV, and B0 are related to SHV. For theclean sea, Bragg scattering is dominated for sea surface, SHH andSVV are highly correlated, SHV is small, so |C|>B0 (Nunziata et al.,2008). For the oil slick, SHH and SVV are weakly correlated, so|C|<B0 (Nunziata et al., 2008).3.3  Eigenvalues of simplified coherency matrixFor natural medium, such as soil and forest, the correlationbetween the co-polarization and the cross-polarization is nearly0 under the reflecting symmetry hypothesis (Nghiem et al., 1992;Allain et al., 2005; Wang et al., 2015).The scattering matrix based on Pauli basis is expressed as=£SHH+ SVVSHH ¡SVV2SHV¤: (9) The coherency matrix of polarization SAR data is=¤¤T=122664jx1j2x1x2¤ 2x1SHV¤x2x1¤jx2j22x2SHV¤2SHVx1¤ 2SHVx2¤ 4jSHVj23775; (10) where x1=SHH+SVV, x2=SHH-SVV.The simplified coherency matrix considering the reflectingsymmetry hypothesis is=122664jx1j2x1x2¤ 0x2x1¤jx2j200 0 4jSHVj23775: (11) The eigenvalue could be acquired by Eigen decomposition(Guissard, 1994):1; nos=12(x3 + r(x4)2+ 4Dj SHHSVV¤j2E); (12) 2; nos=12(x3¡r(x4)2+ 4Dj SHHSVV¤j2E); (13) ¸3; nos= 2Dj SHVj2E; (14) x3=Dj SHHj2E+Dj SVVj2E x4=Dj SHHj2E ¡ Dj SVVj2where  , E. Thefirst and second eigenvalues of the simplified coherency matrixare related to co-polarization backscatter and correlation coeffi-cient, and the third one is related to the multi-scattering of roughsurfaces corresponding to the cross-polarization channel. For theclean sea, λ1, nos>λ3, nos due to the low cross-polarization intensity;for the oil slick, the expression of λ1, nos is too complex to give dir-ect answer which one is larger for λ1, nos and λ3, nos. A detailed ana-lysis would be carried out in the following experiments.4  Data analysis4.1  Analysis of three polarization parametersThe eight Radarsat–2 SAR images are divided into two groups.Group 1 includes No. 1 to No. 4 images in Table 1, with an incid-ence range of 30°–36° and the NESZ of –33 to –36 d B. The fifth toeighth images are Group 2 with an incidence range of 40°–50°and the NESZ of –31 to –34 d B. First, one typical SAR image ischosen from each group respectively for analysis. The SAR imageacquired on May 15, 2010 from the Gulf of Mexico is chosen fromGroup 1, and a SAR image of the Gulf of Mexico on May 8, 2010 ischosen from Group 2, as shown in Fig. 1. The dark patches in Fig. 1aare oil slicks with an image incidence angle of 29°– 31° and thewind speed of 9 m/s. The dark patches in Fig. 1b are also oilslicks, with an incidence angle of 42°–45° and the wind speed of6.5 m/s (Li et al., 2013).To analyze the noise level of the two images, the signal-noise-ratio (SNR, rsn) probability density function (pdf) is plotted in Fig. 2,where the full line stands for the oil slick and dashed line for theclean sea. SNR is calculated by rsn=σ0–na, where σ0 is the backs-cattering intensity and na the averaged NESZ. The noise level ofthe two images are –33.3 to –35.6 and –32 to –33 d B respectively.The co-polarization channel of the SAR data in the Fig. 1a has alarge backscatter intensity, and the averaged VV backscatter in-tensity of the oil slick is –24 d B and the clean sea –15 d B, so thecorresponding averaged signal of the clean sea and oil slick inFig. 2a is above the noise level. The backscatter intensity of the oilarea in Fig. 1b is weak and the corresponding averaged signal ofoil in Fig. 2b is below the noise level.At first we compare the conformity parameters of the oil slickand the clean sea in the two typical SAR images. The conformitycoefficient is analyzed combined with co-polarization phase dif-ference as shown in Fig. 3. Figure 3a gives the co-polarizationphase difference pdf of the SAR data on May 15, where the cleansea has smaller standard deviation than the oil slick. The corres-ponding conformity coefficient is larger than that of oil (Fig. 3c).Please note that both the clean sea and the oil slick have the pos-itive conformity coefficient, indicating that conformity coeffi-cient cannot be simply used for the discrimination of the oil slickand the clean sea. The positive or negative conformity coefficientdoes not absolutely indicate the clean sea or oil slick. The case ofthe SAR data on May 8 is given in Figs 3b and d, where the co-po-larizations are highly correlated for the clean sea area with a nar-row pdf and the co-polarization phase difference pdf of oil isnearly uniform distribution, indicating the co-polarizations areuncorrelated for oil. The corresponding conformity coefficient ofoil is negative and the clean sea positive (Fig. 3d). Consideringthe incidence angle of the two images, for a medium incidenceangle (≈30°), the averaged SNR of oil is above 0, and the conform-ity coefficient is positive; for a large incidence angle (≥40°), theaveraged SNR of oil is below 0, and the conformity coefficient ispositive. The wind speeds of the two images are medium to highspeeds (6–9 m/s). The case of low wind will be discussed later.Next, we compare the Muller matrix parameters (|C|, B0) andeigenvalues of simplified coherency matrix (λ1, nos, λ3, nos). The |C|,B0 parameters of the oil slick and the clean sea in SAR data onMay 15 and May 8, 2010 are given in Fig. 4, with the full line foroil, the dashed line for clean sea, thin line for |C|, bold line for B0.|C| is related to the co-polarization and B0 is related to the cross-polarization. Both oil and clean sea satisfy |C|>B0 and positive  SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87 79C|–B0 in the SAR data on May 15, 2010. The clean sea has thepositive value for |C|–B0, while the oil slick has negative |C|–B0 inMay 8, 2010 data. Large difference between the oil slick and theclean sea is found in |C| parameter; while B0 for the oil slick andthe clean sea is nearly the same. Figure 5 compares the eigenval-ues of simplified coherency matrix, where the thin line stands forλ1, nos, the bold line for λ3, nos, the full line for oil, and the dashedline for clean sea. For the SAR data on May 15, 2010, both oil andclean sea satisfy λ1, nos>λ3, nos and positive λ1, nos–λ3, nos; for the dataon May 8, 2010, the clean sea satisfies λ1, nos>λ3, nos and positivevalue for λ1, nos–λ3, nos, while for the oil slick, λ1, nos and λ3, nos are al-most the same.The comparison of the three polarization SAR parametersshows that they have consistent performance in the same images.For oil slick and clean sea samples, when conformity coefficientis positive, Muller matrix parameters |C|>B0 and eigenvalues ofsimplified coherent matrix λ1, nos>λ3, nos; when conformity coeffi-cient is negative, |C|<B0 and λ1, nos, λ3, nos are nearly the same. Theformulations of the parameters in Section 3 also indicate thesame characterization of the relative magnitude of co-polariza-tion and cross-polarization. Consequently, conformity coeffi-cient has been chosen as a typical parameter to analyze the influ-ence of observing conditions, environmental parameters and im-age noises in detail.4.2  Influence of observing conditions, environmental parametersand image noises on polarization parametersThe influence of the observing conditions, the environmentalparameters and the image noises on polarization parameters hasbeen analyzed. In addition to the two images in Section 4.1, an-other six images are also used as shown in Fig. 6, where the oilslick, clean sea and look likes samples are labeled. Figure 6a isthe image acquired during 2011 Norwegian oil-on-water exer-cise, and the dark patches from the left to the right are plant oil,emulsion and crude oil (chosen for analysis), with a wind speedof 1.6–3.3 m/s (Migliaccio et al., 2011). Figure 6b is a South ChinaNRCS/dB-35-30-25-20-15-10-50aNRCS/dB-35-30-25-20-15-10-50b Fig. 1.   VV polarization images of the SAR data acquired on May 15 and May 8, 2010.-40 -30 -20 -10 0 10 20 30 4000.010.020.030.040.050.060.070.080.09SNR/d Bpdfoil slickclean seaa-40 -30 -20 -10 0 10 20 30 4000.010.020.030.040.050.060.070.080.09SNR/d Bpdfoil slickclean seab Fig. 2.   The VV polarization SNR pdf of the oil slick (full line) and the clean sea (dashed line) of the SAR data: the image on May 15,2010 (a) and the image on May 8, 2010 (b).80 SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87  Analysis of impacting factors on polarimetric SAR oilspill detectionSONG Shasha1, 2, ZHAO Chaofang1, 3*, AN Wei2, LI Xiaofeng4, WANG Chen11 College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China2 Post-doctoral Station, China Offshore Environmental Services Ltd., Tianjin 300457, China3 Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science andTechnology (Qingdao), Qingdao 266100, China4 National Oceanic and Atmospheric Administration, Maryland 20740, USAReceived 8 November 2017; accepted 5 February 2018© Chinese Society for Oceanography and Springer-Verlag Gmb H Germany, part of Springer Nature 2018AbstractPolarimetric synthetic aperture radar (SAR) oil spill detection parameters conformity coefficient (μ), Mullermatrix parameters (|C|, B0), the eigenvalues of simplified coherency matrix (λnos) and the influence of SARobserving parameters, ocean environment and noise level are investigated. Radarsat-2 data are used to makesystematic analysis of polarimetric parameters for different incidences, wind speeds, noise levels and the oceanphenomena (oil slick and look likes). The influence of the SAR observing parameters, the ocean environment andthe noise level on the typical polarimetric SAR parameter conformity coefficient has been analyzed. The resultsindicate that conformity coefficient cannot be simply used for oil spill detection, which represents the imagesignal to the noise level to some extent. When the signals are below the noise level for the oil slick and the looklikes, the conformity coefficients are negative; while the signals above the noise level corresponds to positiveconformity coefficients. For dark patches (low wind and biogenic slick) with the signal below the noise,polarization features such as conformity coefficient cannot separate them with oil slick. For the signal above thenoise, the oil slick, the look likes (low wind and biogenic slick) and clean sea all have positive conformitycoefficients, among which, the oil slick has the smallest conformity coefficient, the look likes the second, and theclean sea the largest value. For polarimetric SAR data oil spill detection, the noise plays a significant role. So thepolarimetric SAR data oil spill detection should be carried out on the basis of noise consideration.Key words: multi-polarimetric SAR, oil spill, conformity coefficient, noiseCitation: Song Shasha, Zhao Chaofang, An Wei, Li Xiaofeng, Wang Chen. 2018. Analysis of impacting factors on polarimetric SAR oil spilldetection. Acta Oceanologica Sinica, 37(11): 77–87, doi: 10.1007/s13131-018-1335-91  IntroductionThe development of satellite remote sensing technology hasbrought up more and more polarimetric SAR data to us, from theSIR-C of US space shuttle, Radarsat-2, Terra SAR, ALOS PALSAR,UARSAR, China GF-3 and so on. The investigation of the polari-metric SAR data for oil spill monitoring has been carried outwidely. Proposed polarimetric SAR oil spill detection methods in-clude coherent matrix eigen composition, Muller matrix para-meters, co-polarized phase difference standard deviation, andthe conformity coefficient and so on (Nunziata et al., 2008, 2015;Migliaccio et al., 2009, 2011, 2012; Zhang et al., 2011; Liu et al.,2011; Li et al., 2013, 2017; Buono et al., 2016; Song et al., 2017).There is a promising application for the polarimetric SAR data oilspill detection.Although many methods for the polarimetric SAR oil spill de-tection have been proposed, the determination criteria of oilslick, free surface and look likes under different observing condi-tions and ocean environment are inconsistent. Especially, thereis the lack of systematic analysis of the noise influence on the po-larimetric SAR oil slick detection. The currently used polarimet-ric SAR data are featured with different noise levels, dependingon antenna patterns, remitting power and receiver noise (Velottoet al., 2011). For example, the different modes of Terra SAR-Xhave the noises between –19 and –26 d B, an averaged noise forALOS PALSAR –30 d B, Radarsat–2 (–36.5±3) d B, C band of SIR-C/X SAR –28 d B and UAVSAR –35 to –53 d B (Nunziata et al., 2012,2013; Minchew et al., 2012). Velotto Domenico et al. (2011) usedtwo polarized Terra SAR-X images to analyze the influence of thenoise on co-polarization phase difference, and pointed out thatmost low SNR pixels came from oil. Minchew Brent used the po-larimetric SAR data for deep water horizon oil spill analysis andproposed that additive noise could be featured using the fourtheigenvalue of T4 matrix. Skrunes Stine et al. (2014) comparedNRCS (normalized radar cross section) and NESZ (noise equival-ent sigma zero) of co-polarization and cross-polarization chan-nels of the clean sea surface, plant oil, emulsified oil and crudeoil using two Radarsat–2 images acquired with different incid-ences in Norwegian oil-on-water exercise in June 2011. The res-ult shows that cross-polarization is significantly influenced bynoises with averaged SNR –2 d B, so co-polarization is chosen forpolarization parameters extraction and oil detection. The co-po-larization data could reduce the impacts of the noise to some ex-tent, but the noise still could not be ignored at all. Additionally,the co-polarization coherency matrix could not make full use of  Foundation item: The Shandong Natural Science Joint Foundation of China under contract No. U1606405.*Corresponding author, E-mail: zhaocf@ouc.edu.cn ea image on July 13, 2008, where the internal waves and the lowwind area are clearly visible and the wind speed is 2.0–3.0 m/s ac-cording to the NCEP forecast wind. Figure 6c is another SouthChina Sea image on August 18, 2012, also with the internal wavesand the low wind area clearly visible, and wind speed of 2.0–2.3 m/s from the NCEP data. The incidence angles of the abovethree images range from 29° to 36°, with a noise level of –33 to –36 d B.Figure 6d shows a South China Sea image on August 13, 2012,where the dark patches are biogenic slicks and the wind speed is3.0–5.0 m/s from the NCEP data. Figure 6e is a Bohai Sea imageon May 16, 2011, where the left bottom is the look alikes, with awind speed of 3.0–5.0 m/s from the NCEP data. Figure 6f gives theSAR image of South China Sea on August 23, 2008, where the in-ternal waves are visible and the wind speed is 3.0 m/s from the-4 -3 -2 -1 0 1 2 3 400.20.40.60.81.01.21.4Phase difference between HH and VV polarizationspdfoil slickclean seaa-4 -3 -2 -1 0 1 2 3 400.10.20.30.40.50.60.7Phase difference between HH and VV polarizationspdfoil slickclean seab-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1.0030oil slickclean sea-1.0 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1.0024681012Conformity coefficientpdfoil slickclean sea-1.0510152025Conformity coefficientpdfc d Fig. 3.   Co-polarization phase difference and conformity coefficient of oil slick and clean sea for SAR data on May 15 and May 8, 2010.2010-05-15 co-polarization phase difference pdf (a), 2010-05-08 co-polarization phase difference pdf (b), 2010-05-15 conformitycoefficient pdf (c) and 2010-05-08 conformity coefficient pdf (d).20 40 60 80 100 120 140 160 180 200051015Pixela0 20 40 60 80 100 120 140 160 180 20001234Pixelb|C|, B0(105)|C|-oilB0-oil|C|-waterB0-water|C|, B0(104)|C|−oilB0−oil|C|−waterB0−water Fig. 4.   Muller matrix parameters of polarization SAR data on May 15 and May 8, 2010: |C| and B0 of SAR data on May 15, 2010 (a) and|C| and B0 of SAR data on May 8, 2010 (b).  SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87 81CEP data. The incidence angles of the three images are 40°–50°and the noise level is –31 to –34 d B.For the purpose of identifying the relationship between theconformity coefficient and the SAR observing conditions, the en-vironmental parameters and the noise levels, VV polarizationSNR, the co-polarization phase and the conformity coefficientpdfs are plotted in Figs 7–12. The VV polarization SNR pdf char-acterizes the signal and noise of the oil slick, look likes and clean0 20 40 60 80 100 120 140 160 180 200246810Pixelb20 40 60 80 100 120 140 160 180 2000123Pixelaλ1, nos, λ3, nos/106λ1, nos-oilλ3, nos-oilλ1, nos-waterλ3, nos-waterλ1, nos-oilλ3, nos-oilλ1, nos-waterλ3, nos-waterλ1, nos, λ3, nos/104 Fig. 5.   Eigenvalue λ1, nos and λ3, nos of simplified coherency matrix of SAR data on May 15 and May 8, 2010: eigenvalue of simplifiedcoherency matrix of SAR data on May 15, 2010 (a) and eigen value of simplified coherency matrix of SAR data on May 8, 2010 (b).0-5-10-15-20-25-30-350-5-10-15-20-25-30-350-5-10-15-20-25-30-35NRCS/dBNRCS/dBNRCS/dB0-5-10-15-20-25-30-350-5-10-15-20-25-30-350-5-10-15-20-25-30-35NRCS/dBNRCS/dBNRCS/dBa b cd e f Fig. 6.   Another six Radarsat-2 images used for analysis. The image on June 8, 2011 (a), the image on July 13, 2008 (b), the image onAugust 18, 2012 (c), the image on August 13, 2012 (d), the image on May 16, 2011 (e) and the image on August 23, 2008 (f).82 SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87  00.020.040.060.080.1000.020.040.060.08pdflook likesclean sealook likesclean sealook likesclean seaa00.10.20.30.40.5pdfb204681012pdfc-40 -30 -20 -10 0 10 20 30 40SNR/d B-4 -3 -2 -1 0 1 2 3 4Phase difference between HH and VV polarizations-1.0-0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1.0Conformity coefficient Fig. 10.   Polarization parameter pdfs of look likes and clean sea of Radarsat-2 data on August 13, 2012(full line for look likes, dashedline for clean sea). SNR pdf (a), co-polarization phase difference pdf (b) and conformity coefficient pdf (c).-40 -30 -20 -10 0 10 20 30 4000.010.020.030.040.050.060.070.080.09SNR/d Bpdfoil slickclean seaoil slickclean seaoil slickclean seaa−4 −3 −2 −1 0 1 2 3 400.20.40.60.81.01.21.4Phase difference between HH and VV polarizationspdfb-1.0-0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1.00510152025Conformity coefficientpdfc Fig. 7.   Polarization parameter pdfs of oil slick and clean sea of Radarsat-2 data on June 8, 2011 (full line for oil slick, dashed line forclean sea). SNR pdf (a), co-polarization phase difference pdf (b) and conformity coefficient pdf (c).00.010.020.030.040.050.060.070.080.09pdflook likesclean sealook likesclean sealook likesclean seaa00.10.20.30.40.50.60.70.80.9pdfb024681012141618pdfc-40 -30 -20 -10 0 10 20 30 40SNR/d B−4 −3 −2 −1 0 1 2 3 4Phase difference between HH and VV polarizations-1.0-0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1.0Conformity coefficient Fig. 8.   Polarization parameter pdfs of look likes and clean sea of Radarsat-2 data on July 13, 2008 (full line for look likes, dashed linefor clean sea). SNR pdf (a), co-polarization phase difference pdf (b) and conformity coefficient pdf (c).00.010.020.030.040.050.060.070.080.09pdflook likesclean sealook likesclean sealook likesclean seaa00.51.01.5pdfb051015202530pdfc-40 -30 -20 -10 0 10 20 30 40SNR/d B−4 −3 −2 −1 0 1 2 3 4Phase difference between HH and VV polarizations-1.0-0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1.0Conformity coefficient Fig. 9.   Polarization parameter pdfs of look likes and clean sea of Radarsat-2 data on August 18, 2012 (full line for look likes, dashedline for clean sea). SNR pdf (a), co-polarization phase difference pdf (b) and conformity coefficient pdf (c).  SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87 8300.010.020.030.040.050.060.070.080.09pdflook likesclean sealook likesclean sealook likesclean seaa0.100.20.30.40.50.60.7pdfb20468101214pdfc-40 -30 -20 -10 0 10 20 30 40SNR/d B-4 -3 -2 -1 0 1 2 3 4Phase difference between HH and VV polarizations-1.0-0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1.0Conformity coefficient Fig. 11.   Polarization parameter pdfs of look likes and clean sea of Radarsat-2 data on May 16, 2011 (full line for look likes, dashed linefor clean sea). SNR pdf (a), co-polarization phase difference pdf (b) and conformity coefficient pdf (c).00.010.020.030.040.050.060.070.080.09pdflook likesclean sealook likesclean sealook likesclean seaa0.0500.100.150.200.250.300.350.400.450.50pdfb1023456789pdfc-40 -30 -20 -10 0 10 20 30 40SNR/d B−4 −3 −2 −1 0 1 2 3 4Phase difference between HH and VV polarizations-1.0-0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1.0Conformity coefficient Fig. 12.   Polarization parameter pdfs of look likes and clean sea of Radarsat-2 data on August 23, 2008 (full line for look likes, dashedline for clean sea). SNR pdf (a), co-polarization phase difference pdf (b) and conformity coefficient pdf (c).Table 2.   Summary of analysis resultsNo. Date Incidence angle/(°) Wind speed/m·s–1Conformity coefficient Averaged SNR/d BDark patch Clean sea Dark patch Clean sea1 2010–05–15 29.2–30.9 9.0 oil slick μ>0 μ>0 rsn>0 rsn>02 2011–06–08 34.5–36.1 1.6–3.3* oil slick μ>0 μ>0 rsn>0 rsn>03 2008–07–13 34.4–36.0 2.0–3.0 low wind μ<0 μ>0 rsn<0 rsn>04 2012–08–18 29.2–30.9 2.0–2.3 low wind μ<0 μ>0 rsn<0 rsn>05 2011–05–16 43.6–44.9 2.0–3.0 low wind μ>0 μ>0 rsn>0 rsn>06 2010–05–08 41.9–43.3 6.5 oil slick μ<0 μ>0 rsn<0 rsn>07 2012–08–13 48.3–49.5 3.0–5.0 biogenic slick μ<0 μ>0 rsn<0 rsn>08 2008–08–23 40.1–41.6 3.0 low wind μ<0 μ>0 rsn<0 rsn>084 SONG Shasha et al. Acta Oceanol. Sin., 2018, Vol. 37, No. 11, P. 77–87