Sea Oil Slick Observation Using Hybrid-Polarity SAR Architecture

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Sea Oil Slick Observation Using Hybrid-PolaritySAR Architecture

Ferdinando Nunziata, Senior Member, IEEE, Maurizio Migliaccio, Senior Member, IEEE, andXiaofeng Li, Senior Member, IEEE

Abstract�—In this study, hybrid-polarity (HP) architecture isexploited to observe sea oil slicks. HP features are interpreted interms of sea surface scattering with or without oil slicks, underlow-to-moderate wind conditions. They are shown to exhibit adifferent sensitivity with respect to slick-free, weak-dampingslick-covered, and oil-covered sea surfaces. This sensitivity isveried against HP measurements obtained transforming actualL- and C-band quad-polarimetric synthetic aperture radar (SAR)data where both oil slicks and weak-damping look-alikes arepresent. Experiments demonstrate: 1) the remarkable perfor-mance of HP features to both observe oil slicks and distinguishingthem from weak-damping look-alikes; 2) the marginal effectplayed by the sensor�’s noise oor on HP features performance;3) the pronounced sensitivity of the HP features to the dampingproperties of the surfactants; and 4) the comparable performancethat characterizes polarimetric entropy derived by HP and con-ventional polarimetric measurements.

Index Terms�—Hybrid polarity (HP), oil spill, polarimetric scat-tering, synthetic aperture radar (SAR).

I. INTRODUCTION

T HERE is a general consensus that the unique capabilitiesof full-polarimetric (FP) synthetic aperture radar (SAR)

play a key role in geophysical remote sensing. An FP SAR,mea-suring the whole scattering matrix for each resolution cell, pro-vides valuable and unique information that allows classifyingthe scattering mechanisms of the observed scene. Hence, FPfeatures allow generating value-added products that are morephysically reliable and robust than the single-polarization onesin a broad range of thematic domains that include forests, agri-culture, urban, cryosphere, and ocean [1].However, the unprecedented level of scattering details pro-

vided by an FP SAR comes at a cost in terms of doubled average

Manuscript received February 21, 2014; revisedMay 22, 2014; acceptedMay30, 2014. This work was supported in part by the ESA-MOSTDragon-3 cooper-ation project 10689; by the Shanghai Municipal Science and Technology Com-mission under Grant 13dz12044000; and by the NOAA Ocean Remote Sensing(ORS) Program funding. The views, opinions, and ndings contained in this re-port are those of the authors and should not be construed as an ofcial NOAAor U.S. Government position, policy, or decision.Associate Editor: R. Romeiser.F. Nunziata and M. Migliaccio are with the Dipartimento di Ingegneria, Uni-

versità degli Studi di Napoli Parthenope, Napoli 80143, Italy (e-mail: [email protected]; [email protected]).X. Li is with GST at the National Environmental Satellite, Data, and Infor-

mation Service (NESDIS), National Oceanic and Atmospheric Administration(NOAA), Camp Springs, MD 20746 USA (e-mail: [email protected]).Color versions of one or more of the gures in this paper are available online

at http://ieeexplore.ieee.org.Digital Object Identier 10.1109/JOE.2014.2329424

transmitted power, halved swath width, and limited range of ad-missible incidence angles, with respect to a single-/dual-polar-ization SAR [2].To mitigate those drawbacks, compact polarimetry (CP) ar-

chitectures have been proposed since they provide polarimetricperformance that is expected to be close to the one related toFP SARs, while avoiding their principal drawbacks. The ideathat lies at the basis of CP architecture is transmitting only onepolarization while receiving coherently, i.e., both amplitudeand the relative phase, according to an orthogonal polarizationbasis. Hence, CP architectures belong to the class of dual-po-larimetric coherent SARs. A conventional dual-polarimetriccoherent SAR transmits one linear polarization (horizontalor vertical ) while receiving coherently according to the

orthogonal basis. This architecture suffers from a majordisadvantage: the relative phase between the - and -polarizedreturns is practically uninformative over natural distributedtargets. Hence, only limited information on the scattering scenecan be retrieved. This disadvantage can be overcome usingthree CP architectures, namely the , the circularly�–circu-larly (CC), and the hybrid-polarity (HP) architecture. The rstone consists of transmitting a linearly polarized slant eld,i.e., at 45 angle relative to the or polarization, whilereceiving coherently according to the linear basis [3].However, the linear 45 transmission does not always ensureorientation invariance for double-bounce responses [4], [5]. Tohave a backscattered eld rotationally robust with respect tothe shape of the observed scene, a circular polarization mustbe transmitted. Hence, an alternative CP architecture can beimplemented transmitting a circularly polarized eld whilereceiving coherently according to a dual-circularly polarizedbasis (CC). CC architecture is not easy to be implemented.A valuable alternative is rst proposed in [5], where an HParchitecture is introduced that consists of transmitting a circu-larly polarized eld while receiving coherently according to alinear basis. The underpinning idea is based on the factthat fundamental principles of polarimetric optics state that thecovariance matrix does not depend on the polarization basis ofthe receiver. Hence, given a circularly polarized illumination,the same covariance matrix is obtained using measurementscollected by either a circularly polarized or a linear coherentbasis [6]. As a matter of fact, HP architecture retains all theadvantages of the CC one, while leading to a simpler hardwareimplementation [5], [7]. In addition, HP architecture is alsocharacterized by specic advantages that include self-calibra-tion, comparable signal levels on the receiver channels, limited

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effect of crosstalk or ambiguities, reduced impact of Faradayeffect, etc. [4], [5], [7]�–[9].Currently, the Indian mission RISAT-1, launched in 2012,

is equipped with a polarimetric C-band SAR that implementsthe HP mode. The polarimetric SAR operated by the JapaneseALOS-2 mission, launched on May 24, 2014, allows both the

mode and the HP mode, and the future Radarsat Constella-tion Mission (RCM) will operate the HP mode [10].To analyze SAR data collected in the CP mode, two strategies

are possible: reconstructing a pseudo FP signature or character-izing the polarization properties of the scattered wave under acircular-polarization illumination to infer the scattering proper-ties of the observed scene. This latter approach was proposed in[5] and [6], where the so-called decomposition was in-troduced and applied to analyze CP SAR data collected by thetwo mini-radio-frequency (mini-RF) radars own in near-polarlunar orbits and operating in the HP mode.In the literature, the rst applicative study on the use of CP

SAR data for oil slick observation was proposed in [11], wherethe capability of the degree of polarization to jointly observeoil and target at sea was investigated under different polariza-tions, including HP and architecture. Experiments, under-taken using L- and C-band SAR data, showed the superiority ofCP architecture with respect to conventional dual-polarizationSAR modes.In this study, following the rationale proposed in [5], the

HP architecture is exploited to observe oil at sea. A modelis rst proposed to support the physical understanding of thepolarimetric sea surface scattering with and without surfaceslicks, under low-to-moderate wind conditions, in terms ofsome HP-related features, hereinafter HP features. The modelis veried against HP measurements obtained transformingactual quad-pol SAR data to replicate the circularly polarizedtransmission and coherent reception. Actual L- andC-band single look complex (SLC) SAR data collected byALOS-PalSAR and RADARSAT-2 missions are processedwhere both well-known oil slicks and look-alikes are present.Experiments demonstrate the effectiveness of the proposedapproach to both observe oil slicks and distinguish them fromweak-damping look-alikes. As far as conventional polarimetricapproaches go [12], HP features show a pronounced sensitivityto the damping properties of the surfactants. Along with the HPfeatures, a conventional FP feature (the polarimetric entropy)is used as reference, and it is contrasted with the correspondentHP feature. Results demonstrate that polarimetric entropyderived by FP and HP measurements provides comparableperformance.The remaining of this paper is organized as follows. In

Section II, polarimetric background is reviewed and the polari-metric scattering model is described. In Section III, experimentsare presented and discussed, while the conclusions are drawnin Section IV.

II. POLARIMETRIC MODEL

In this section, the proposed polarimetric model is described.To provide an effective description, the section presents a brief

primer on wave polarimetry, which is the backbone of the pro-posed approach. Then, the section is divided into two parts out-lining the fundamental concepts of HP architecture and the pro-posed polarimetric scattering model.In response to an almost-monochromatic illumination of a

given polarization, the randomly uctuating electromagneticwave scattered off a distributed scene presents polarizationproperties that fall between two extremes: fully polarized andunpolarized [13]. A fully polarized wave is such that the endpoint of the electric eld traces out an ellipse (or degenerateforms) conned to the polarization plane. An unpolarized waveis such that the end point of the electric vector moves in anirregular way for increasing time. However, fully polarized andunpolarized are two extreme cases; real electromagnetic waves,generally, have components of both and turn out to be partiallypolarized.The description of the polarization properties of a partially

polarized wave relies on second-order eld correlation proper-ties. The latter can be accounted for using the coherence matrixthat contains all the information on the state of polarization ofthe wave, including the intensity. The 2 2Hermitian and semi-positive�–denite coherency matrix associated with an electro-magnetic wave , whose components along an orthogonalbasis are , is given by [13]

(1)

where a temporal dependence is understood; and ,, and stand for ensemble average, complex conjugate trans-pose, and complex conjugate, respectively. The diagonal ele-ments are the spectral densities or, loosely speaking, theintensities associated to the eld component . The trace ofthe matrix is the total spectral density ofthe eld. Moreover, . The off-diagonal elements ofrepresent the correlation prevailing between the mutually or-

thogonal components of the electric eld. Hence, a complex cor-relation coefcient can be dened as follows [13]:

(2)

where is the relative phase between the and eld com-ponents, and stands for modulus. It can be easily shown that

. Moreover, the sign of indicates right-handside (negative) or left-hand side (positive) polarization [13],[14].An unpolarized wave is such that independently of

the particular choice of the - and -axis. Hence, it calls for acoherence matrix proportional to the identity matrix [13]

(3)

where is the 2 2 identity matrix, and

(4)

A fully polarized wave is characterized by a coherence matrixwhose determinant vanishes: [13]. This implies thatthe orthogonal eld�’s components are completely correlated,


NUNZIATA et al.: SEA OIL SLICK OBSERVATION USING HYBRID-POLARITY SAR ARCHITECTURE 3

i.e., . A fully polarized eld is also said to be ellipti-cally polarized, i.e., the end point of the electric eld describesan ellipse which can reduce to a circle (circular polarization) orto a straight line (linear polarization).A partially polarized wave contains both fully polarized and

unpolarized components, and it is characterized by .One synthetic and partial way to characterize its polarizationproperties is measuring the degree of polarization; i.e., the relative intensity of the polarized component to theintensity of the total eld [16], [17]

(5)

Since the trace and determinant are invariant with respect uni-tary transformations, is independent on the transverse refer-ence frame. When equals the limiting values 0 and 1, the lim-iting cases of unpolarized and fully polarized elds are attained.Alternatively, one can determine how unpolarized is the waveby using the entropy [13]

(6)

where . When equals the limiting values 0 and1, the limiting cases of fully polarized and unpolarized elds areattained. The entropy can be also related to [18]

(7)

It can be noted that is a monotonic function of , the max-imum ( ) is achieved for and corresponds to anunpolarized eld (completely random eld), and the minimum( ) is achieved for and corresponds to a fullypolarized eld (completely deterministic eld).

A. HP Architecture

In this section, the coherence matrix associated with the scat-tered wave received by a SAR implementing theHP architectureis simulated starting from the scattering matrix measured by anFP SAR [7], [8].A SAR implementing the HP architecture transmits a circular

polarized wave and receives coherently two orthogonal linearpolarizations. This conguration has been successfully used

by the lunar mini-RF radars [7], [8]. In this study, it is assumedthat a right-hand circular (RHC) polarization is transmitted. Thelinearly polarized received eld is simulatedfrom the FP scattering matrix according to [5]

(8)

where with is the complex scattering ampli-tude.

TABLE IEXPECTED BEHAVIOR OF THE HP FEATURES FOR SLICK-FREE

AND OIL-COVERED SEA SURFACES

Once the received eld is obtained, can be straightfor-wardly constructed. In detail, the elements of (1) are given by

(9)

Hence, several quantitative parameters can be derived [6].Those parameters include (4), (5), (6), and(2), and the circular polarization ratio

(10)

where stands for imaginary part. Equation (10) is the ratio ofthe same-sense to opposite-sense circular polarization receivedpower [5].

B. Sea Oil Slick Observation

In this section, the aforementioned parameters are interpretedin terms of sea surface scattering with or without oil slicks,under low-to-moderate wind conditions.In case of the slick-free sea surface, the dominant scattering

mechanism is the Bragg or tilted Bragg one; which is a quasi-de-terministic single-bounce scattering mechanism. Hence, it re-sults in a scattered wave whose polarization properties are ex-pected to be very close to the ones associated with a fully polar-ized wave: and close to unity, and close to zero.Moreover, the single-bouncing nature of the Bragg scatteringimplies that, in response to an RHC illumination, the scatteredwave is left-hand-circularly (LHC) polarized. Hence, positive

values are expected, whose statistical distribution shouldpeak around 90 .In case of the oil-covered sea surface, due to its strong

damping properties, the Bragg resonant waves are signicantlyreduced, leading to a non-Bragg mechanism, as demonstratedin [19]�–[29]. The latter results in a scattered wave whoseintensity is signicantly lower than the one associated with thefree-sea surface and whose polarization properties are expectedto be close to the ones that characterize an unpolarized wave:



TABLE IISAR DATA SET

Fig. 1. ALOS�–PALSAR SAR data collected on January 10, 2008, at 04:29:18 UTC in Gulf of Mexico. (a) Squared modulus -polarized image, (b) image,(c) image, (d) image, (e) image, (f) image, (g) image, and (h) binary output.

and close to zero, close to unity, and largervalues. Moreover, both positive and negative values areexpected, witnessing that a high random scattering mechanismis in place, whose distribution is expected to be much broaderthan the slick-free case.According to this theoretical rationale, slick-free and oil-cov-

ered sea surfaces are expected to have disjoint HP features; seeTable I. Moreover, the two scenarios are expected to call for

distributions peaked around 90 (slick-free), andmuch broader (oil-covered). Hence, mimicking the rationale de-

veloped in [21] and [25], where the standard deviation of thecopolarized phase difference (CPD)was related to slick-free andoil-covered sea surface scattering, in this study the standard de-viation of , hereinafter termed to as , is rst introduced,and it is expected to exhibit a different sensitivity to slick-free(low ) and oil-covered (high ) sea surfaces; see Table I.A polarimetric behavior similar to the slick-free sea surface

one is expected to apply when a weak-damping look-alike ispresent, as demonstrated in [19]�–[27]. In this case, Bragg scat-tering is still in place, although it is characterized by a lower



Fig. 2. Closeup of the image [see Fig. 1(c)] where pixels whose intensityis below NESZ are marked in black.

backscattered signal. Hence, this scenario is expected to be in-distinguishable from the slick-free sea surface in terms of theHP features of Table I. This behavior is advisable in sea oil slickobservation.

III. EXPERIMENTSIn this section, some experiments are detailed and discussed

to demonstrate the effectiveness of the proposed approach toboth observe oil slicks and sort them out of weak-damping look-alikes. Oil slicks considered in this study are relevant to oil seepsand have been already discussed in literature [24], [29], [35]. Apetroleum seep is a place where natural liquid or gaseous hy-drocarbons escape to Earth�’s atmosphere and surface, normallyunder low pressure or ow. Seeps generally occur above ei-ther terrestrial or offshore petroleum accumulation structures.

TABLE IIIMEAN VALUE OF THE HP FEATURES EVALUATED CONSIDERING THE

NOISE-FREE PIXELS BELONGING TO THE SLICK-FREE ANDOIL-COVERED ROIS OF FIG. 1(A)

TABLE IVMEAN VALUES OF AND THAT CHARACTERIZE THE

THREE CLASSES OF FIG. 5

In the Gulf of Mexico, there are more than 600 natural oil seepsthat leak between one and ve million barrels of oil per year[36]�–[38]. All the weak-damping surfactants are related to casesalready discussed in literature [21], [23].In the subsequent experiments, all the polarimetric fea-

tures are estimated using a 5 5 average moving window.Along with the HP features, a conventional FP one, i.e.,the polarimetric entropy, is used for reference. Both L-bandALOS-PalSAR and C-band RADARSAT-2 SLC FP SARdata are processed. For each SAR image, wind information isobtained by ancillary data, i.e., Scatterometer and the NationalOceanic and Atmospheric Administration (NOAA) NationalData Buoy Center (NDBC) information.The rst experiment (see Ex1 in Table II) is relevant to the

SAR data collected in Gulf of Mexico in 2008. Buoy data indi-cate that the wind speed and the signicant wave height duringthe SAR observation were 5.1 m/s and 1.22 m, respectively.The squared-modulus -polarized SAR data are shown

as graytone image in Fig. 1(a). The image area is known torelease natural seeps constantly [30]. Hence, the dark area ofFig. 1(a) is related to the oil slick. The HP features are shown asfalse-color images in Fig. 1(b)�–(g). The image [see Fig. 1(b)]clearly highlights the presence of the oil slick which results in-values larger than the slick-free sea surface ones. This means

that Bragg/tilted-Bragg scattering applies everywhere butwithin the oil-covered sea surface. Hence, as predicted by thetheoretical model, almost fully polarized scattered waves resultfrom the slick-free sea surface, while practically unpolarizedwaves result from the oil-covered sea surface. In addition, theimage shows that a very heterogeneous scattering behavior

applies within the dark area that appears to be uniformly dark



Fig. 3. (a) Empirical pdf of , (b) , (c) , (d) , (e) , (f) , (g) , evaluated within the oil-covered and slick-free ROIs of Fig. 1(a). Pixelswhose intensity is below the NESZ are sorted out.

Fig. 4. Empirical pdf of and evaluated within the oil-covered and slick-free ROIs of Fig. 1(a).

in the single-polarization intensity data of Fig. 1(a). This areacalls for values ranging from 0.1 up to 0.4 witnessing thata surfactant characterized by different damping properties ispresent. It can be noted that the damping properties decreasewhen drifting away from the center of the slick. This behavioris consistent with an oil layer whose damping properties are

Fig. 5. Three classes of the -means unsupervised partitioning method ap-plied to (a) the and (b) the output, respectively. Pixels whose intensityis below NESZ are marked in black.

spatially variable. It must be explicitly pointed out that thisvariability can be easily recognized by using HP features, but it



Fig. 6. ALOS�–PALSAR SAR data collected on March 10, 2007, at 15:19:18 UTC off the coasts of Dà Nang, Vietnam. (a) Squared modulus -polarized image,(b) image, (c) image, (d) image, (e) image, (f) image, (g) image, and (h) binary output.

TABLE VMEAN VALUE OF THE HP FEATURES EVALUATED WITHIN A ROI THAT FITS

THE DARK AREA OF FIG. 6(A) AND AN EQUAL-SIZE SLICK-FREESEA SURFACE ROI. PIXELS WHOSE INTENSITY IS BELOW

THE NESZ ARE SORTED OUT

is hardly to be recognized using single-polarization SAR data.Similar comments apply for the image [see Fig. 1(c)] thatallow the oil/sea discrimination and witness that the slick-freesea surface calls for negligible -values that signicantly

increase within the oil-covered area. Moreover, even theimage shows a signicant granularity which is not clearly vis-ible in the dark area of Fig. 1(a). A similar oil/sea discriminationis obtained using [see Fig. 1(d)], which again highlightsthe random nature of the scattering mechanism associated withthe oil-covered area. The image [see Fig. 1(e)] exhibitsa behavior very close to the one. This can be theoreticallyjustied considering that can be seen as an upper bound for

[16]. Hence, and the equality is obtained onlyand only if [13], [16]. The image [see Fig. 1(f)]conrms the theoretical predictions showing that LHC polar-ized waves result from the slick-free sea surface, while bothLHC and RHC waves result from the oil-covered sea surface. Adeeper analysis of Fig. 1(f) witnesses that negative values,i.e., RHC scattered waves, mainly result from the oiled areacalling for the strongest damping. This behavior is conrmedby the image [see Fig. 1(g)], which shows that the largest

variability ( 50 ) results from that area. Hence,and are mainly sensitive to strong-damping surfactants.Before proceeding further it is important to quantify the effect

of the noise equivalent sigma zero (NESZ) on the performanceof HP features. In fact, the theoretical model predicts a departurefrom Bragg scattering in case of oil slicks which lead to a high



Fig. 7. Empirical pdf of (a) , (b) , (c) , (d) , (e) , (f) , and (g) , evaluated within a ROI that ts the shape of the dark area of Fig. 6(a)well.

TABLE VIMEAN VALUE OF THE HP FEATURES EVALUATED WITHIN THE SLICK-FREE

AND OIL-COVERED ROIS RELATED TO THE EXPERIMENT OF FIG. 8

random scattering mechanism. Hence, to further analyze the ef-

fectiveness of the proposed approach, pixels whose intensity isbelow theALOS�–PalSARNESZ are sorted out. ALOS�–PalSARNESZ varies between 28 and 34 dB [21]. In this experiment,NESZ 27 dB is used as the worst case. To better visualizenoise effects, an enlarged version of the image, which in-cludes the low backscatter area, is shown in Fig. 2. Pixels whoseintensity is below the NESZ are marked in black. It can be notedthat noisy pixels mostly belong to the area calling for larger de-parture from Bragg scattering. The same results apply for all theHP features.To provide amore quantitative analysis on the performance of

the HP feature in discriminating oil-covered from the slick-freesea surface, the empirical probability density functions (pdfs)relevant to the HP features and the squared-modulus -po-larized SAR data and measured within the two region of inter-ests (ROIs) of Fig. 1(a) are shown in Fig. 3. Note that pixelsbelow NESZ are ltered out. The pdfs related to the single-po-larization channel [see Fig. 3(a)] witness that, as expected, the



Fig. 8. RADARSAT-2 SAR data collected on May 8, 2010, at 12:01:27 UTC in Gulf of Mexico. (a) Squared modulus -polarized image, (b) image, (c)image, (d) image, (e) image, (f) image, (g) image, and (h) binary output.

TABLE VIIMEAN VALUES OF AND THAT CHARACTERIZE

THE THREE CLASSES OF FIG. 11

oil-covered sea surface results in lower backscattering. In de-tail, the mean slick-free and oil-covered backscattered valuesare 0.1337 and 0.0873; see Table III. Moreover, slick-free andoil-covered pdfs are partially overlapped witnessing that theoil/sea discrimination can be difcult using single-polarizationintensity data. This result conrms the analysis undertaken in[27] where an FP approach is compared with a single-polariza-tion one. The slick-free and oil-covered pdfs relevant to the HPfeatures are always well separated, as well as their mean values;see Table III. The pdfs relevant to the slick-free HP featuresare always peaked around the values theoretically predicted inTable I. The pdfs relevant to the oil-covered case are signi-cantly broader, conrming the spatial variability of the damping

properties within the oil-covered area. The pdf exhibits acompletely different shape when evaluated within the slick-freeand oil-covered sea surfaces; see Fig. 3(f). As expected, theslick-free pdf peaks around 90 , while a signicantlybroader pdf is obtained in the oil-covered case. This is furtherconrmed by their mean values, 2.4129 and 50.3271 , re-spectively. Moreover, the pdf [see Fig. 3(g)] conrms thespatial variability of the damping properties of the oiled areathat results in values ranging between 20 and 150 . Sincethe slick-free and oil-covered mean values are well sep-arated, a simple logical true (sea) and false (oil) lter can beimplemented using an empirical threshold. In this study, thethreshold 40 is used to obtain the binary image shown inFig. 1(h), which clearly highlights the oiled area calling for thestrongest damping. It can be noted that the HP features followthe predicted theoretical behavior even excluding noisy pixels.Accordingly, since the �“geophysical noise,�” i.e., the one dueto random scattering mechanism, and the noisy pixels, i.e., theones whose intensity is below NESZ, concur only within theoiled area, one may think that pixels above NESZ allow classi-fying the low backscatter area whereas pixels below NESZ onlyallow a better morphological denition of the area.



Fig. 9. Closeup of the image [see Fig. 8(c)] where pixels whose intensityis below NESZ are marked in black.

To further discuss the effectiveness of the HP approach,one of the most employed features in conventional quad-po-larimetric approaches, namely the Cloude�–Pottier polarimetricentropy [21], [27], is here contrasted with the correspondingHP feature, i.e., . Both features are bounded in theinterval and, although they have different physical meanings,they carry similar information on the scattering scene, with

and meaning deterministic andcompletely depolarizing scenarios, respectively. The empiricalpdfs relevant to and are shown in Fig. 4. It can be notedthat both features show remarkable performance in oil-seadiscrimination. To provide a further objective comparison, aconventional unsupervised -means clustering method [31] isapplied to partition and images into three classes. Out-puts in Fig. 5 clearly show that in both cases, the three classescorrespond to: the strong damping oil-covered area (the largest

and values); an intermediate-damping slick-coveredarea that mainly surrounds the previous one (intermediate

TABLE VIIIMEAN VALUE OF THE HP FEATURES EVALUATED WITHIN THE SLICK-FREEAND SLICK-COVERED ROIS RELATED TO THE EXPERIMENT OF FIG. 12

and values); and the slick-free sea surface (the lowestand values); see Table IV. Note also that both features callfor intermediate values even out of the main slick area, i.e., thebottom right-hand side of the image, witnessing that probablya larger oil-affected area is present. It must be noted that all theHP features exhibit the above-described zoning (not shown tosave space), except the image which is mainly sensitiveto the strong-damping oiled area. It must be pointed out thatthe zoning provided by the HP features is physically supportedby the unconventional nature of the oil slicks due to seepages.In fact, in this case, the oil comes from the bottom of the seaand, due to currents, sea state conditions, weathering, etc., itproduces a heterogeneous oil layer in terms of visco-elastic andchemical properties [32].The second experiment (see Ex2 in Table II) is relevant to

the SAR data collected off the coast of Dà Nang, Vietnam, in2007. Quickscat scatterometer data indicate that low-to-mod-erate wind conditions (4 m/s) apply.This experiment was fully detailed in [21], where quad-po-

larimetric techniques were applied to analyze their robustnessagainst marine-related oil look-alikes. An excerpt of thesquared-modulus -polarized SAR data is shown, as agraytones image, in Fig. 6(a). A dark patch related to a marinefeature is present, whose elongated shape may bemisinterpretedas an oil slick in single-polarization SAR data. The imagesrelated to the HP features are shown in Fig. 6(b)�–(g). It can benoted that the look-alike, as predicted by the theoretical model,is practically indistinguishable from the surrounding sea bythe HP features. This latter witnesses that a Bragg/tilted-Braggscattering mechanism is everywhere in place but in few isolatedpoints which, however, belong to both the dark area and thesurrounding sea. It can be noted that, although some featuresrelated to the low backscatter area can be recognized in the ,, and images, only some hints related to the darker

area can be visually recognized by the , , and im-ages. This behavior is further conrmed by the analysis of therelevant pdfs [see Fig. 7(b)�–(g)] that are always overlapped,demonstrating that Bragg scattering is everywhere in place.Even in this case, it can be noted that the pdfs associatedwith , , and show the best overlapping. This resultis further conrmed by the mean values of the HP features



Fig. 10. Empirical pdf of (a) , (b) , (c) , (d) , (e) , (f) , (g) , evaluated within a ROI that ts the shape of the oil slick labeled as �“ �” inFig. 8(a) and an equal-size slick-free ROI well.

listed in Table V. Note that, in this case, no pixel is belowthe ALOS�–PALSAR NESZ. It must be explicitly noted thatthe slick-free and slick-covered pdfs [see Fig. 7(f)] bothpeak around 90 , witnessing that, as predicted by thetheoretical model, LHC polarized scattered waves result fromboth slick-free and slick-covered sea surfaces. In addition,slick-free and slick-covered mean values (see Table V) arevery close to each other. Hence, in this case, the logical lterprovides the output shown in Fig. 6(h) using the same thresholdof the previous case. The two-classes unsupervised -meansclustering (not shown to save space) fails in distinguishingthe look-alike from the surrounding sea using both and. This result conrms that, even in this case, exhibits

performance similar to .The third experiment (see Ex3 in Table II) is relevant to the

SAR scene collected in Gulf of Mexico in 2010. Buoy dataindicate that the wind speed and the signicant wave heightduring the SAR acquisition were 6.5 m/s and 0.68 m, respec-tively. The squared-modulus -polarized SAR data are shownas graytone images in Fig. 8(a). Three dark areas are visible that,since this location is known to release natural oil seeps con-

Fig. 11. Three-class -means unsupervised partitioning method applied to (a)the and (b) the output, respectively. Pixels whose intensity is belowNESZ are marked in black.



Fig. 12. RADARSAT-2 SAR data collected on December 14, 2009, at 14:09:00 UTC off the California coast. (a) Squared modulus -polarized image, (b)image, (c) image, (d) image, (e) image, (f) image, (g) image, and (h) binary output.

stantly [29], [30], are due to oil slicks. HP features are shown,as false-color images, in Fig. 8(b)�–(g). In all the cases, oil slicksare clearly emphasized with respect to the background sea byHP features, witnessing that, as expected, an almost unpolarizedscattered wave results from the oil-covered sea surface. More-over, it can be noted that, although there are threemain oil slicks,the area that results in unpolarized backscattering extends alsoout of the main slicks. In detail, the upper right-hand side ofthe scene results in unpolarized scattered waves ( and

). This area can hardly be recognized in the -po-larized image, unless a proper graytone tuning is undertaken.Even in this case, before proceeding further, it is important to

quantify the effect of the NESZ on the performance of HP fea-tures. Hence, pixels whose intensity is below the RADARSAT-2NESZ are ltered out. RADARSAT-2 NESZ related to the nequad-polarization mode varies between 33.5 and 36.5 dB. Inthis study, NESZ 33.5 dB is used as the worst case. To bettervisualize noise effects, an enlarged version of the image,which includes the low backscatter areas, is shown in Fig. 9.Pixels whose intensity is below the NESZ are marked in black.It can be noted that, although noisy pixels mostly belong to thelow backscatter area, there are many noisy pixels even out of themain slicks. Although no physical explanation is at the moment

available, one may note that, since a moderate wind speed andintermediate incidence angles apply, probably the large numberof noisy pixels out of the main slicks can be explained, con-sidering that the oil seep may have affected a larger area. Onthis purpose, it is worth noting that even the single-polariza-tion intensity image [see Fig. 8(a)] shows very low backscat-tering out of the main slicks. This behavior is also supportedby the values of the HP features that are larger than expectedout of the main oil slicks. The quantitative analysis providedby the HP feature pdfs evaluated over a ROI that ts the darkarea marked with a white star in Fig. 8(a) and an equal-sizeslick-free ROI well, is shown in Fig. 10. It can be noted thatthe slick-free/oil-covered pdfs are now slightly overlapped. Thisis mainly due to the slick-free sea surface backscattering thatis characterized by a depolarization larger than expected (al-though still well distinguishable from the wave resulting fromthe oil-covered sea surface). This means that a slight depar-ture from Bragg/tilted-Bragg scattering applies even over theslick-free sea surface. This behavior is further conrmed by theslick-free/oil-covered mean HP feature values (see Table VI),which shows that, although oil is clearly distinguishable fromthe background sea, the latter calls for ( , , and )values larger (lower) than expected.



Fig. 13. Empirical pdf of (a) , (b) , (c) , (d) , (e) , (f) , and (g) , evaluated within a ROI that ts the shape of the low backscatter areain Fig. 12(a) and an equal-size slick-free ROI well.

This unexpected behavior, as previously discussed, suggeststhat a larger area is actually affected by the oil seepages. Similarresults have been obtained in [12] where the same data set is pro-cessed by conventional polarimetric approaches. Note that thisbehavior cannot be observed by single-polarization SAR data.The slick-free pdf, as expected, peaks around 90and calls for positive values only. The oil-covered pdf is muchbroader and calls for both positive and negative values. As faras for Ex1, even in this case, negligible values mainly resultfrom the main oil slicks. It can be noted that oil-covered andslick-free sea surfaces can be easily distinguished using ,as clearly shown in the binary image of Fig. 8(h), where thesame threshold of the previous cases is adopted. Even in thiscase, the output is contrasted with the conventional one.The three-class -means output obtained processing andis shown in Fig. 11(a) and (b), respectively. Both features

show similar performance in discriminating the three dampingregimes; see Table VII. It can be noted that, as expected, in this

case, the slick-free sea surface calls for larger and valueswith respect to Ex1; see Table IV. This result further conrmsthat a larger oiled area is probably present.The fourth experiment (see Ex4 in Table II) is relevant to

the SAR scene collected off the California coast. Buoy dataindicate that the wind speed and the signicant wave heightduring the SAR acquisition were 5.4 m/s and 1.54 m, respec-tively. This experiment was fully detailed in [23], where quad-polarimetric techniques were applied to analyze their robust-ness against marine-related oil look-alikes. The squared-mod-ulus -polarized SAR data are shown, as a graytone image, inFig. 12(a), where a dark area is present. Although the single-po-larization intensity image may suggest that an oil slick is inplace, this is not actually the case, as witnessed by the HP fea-tures [see Fig. 12(b)�–(g)]. The latter show that an almost fullypolarized wave is scattered off the sea surface everywhere. Theonly exception is the metallic target (bright spot in the -po-larized image) which is well distinguishable from the back-



ground by the HP features. This is because metallic targets gen-erally consist of plane, dihedral and trihedral structures, as wellas dihedral corner reectors and thin wires; hence, they result ina random scattering mechanism [33], [34] that is characterizedby HP features similar to the oil ones. The quantitative analysisundertaken evaluating the pdfs over a ROI that ts the shape ofthe dark area Fig. 12(a) and a slick-free ROI well, is shown inFig. 13. It can be noted that slick-free and slick-covered pdfs arepractically overlapped, witnessing that the two scenarios cannotbe distinguished by HP features. This is further conrmed by thequantitative analysis listed in Table VIII. Even in this case, thebest performance in de-emphasizing the look-alike is providedby , , and . Note that in this case, no pixel is below theNESZ. Moreover, the pdfs are characterized by similarvalues that justify the output of the binary lter [see Fig. 12(h)],where only the metallic target is visible.

IV. CONCLUSIONIn this study, HP architecture is rst exploited to observe

sea oil slicks. HP features are analyzed in terms of sea sur-face scattering with or without oil slicks and weak-dampinglook-alikes and are shown to exhibit a different sensitivitywith respect to the damping properties of the surfactants, underlow-to-moderate wind conditions. Experiments, undertaken onHP measurements obtained transforming quad-polarimetric L-and C-band SAR data conrm model predictions and demon-strate the effectiveness of the proposed approach. The mainnovelties that characterize this study can be summarized asfollows.�• HP features are, for the rst time, interpreted in terms ofsea surface scattering with or without surfactants, underlow-to-moderate wind conditions, and they are shown toexhibit a different sensitivity to slick-free and oil-coveredsea surfaces.

�• Along with standard HP features derived by wave polariza-tion theory, a new parameter, i.e., the standard deviation ofthe phase difference between the and eld components( ), is here proposed to observe sea oil slicks.

�• The large difference between values relevant to slick-free and oil-covered sea surfaces suggests a simple androbust lter to detect strong-damping oil slicks.

�• HP features exhibit a pronounced sensitivity to thedamping properties of the surfactants, allowing a rstmapping of their damping properties.

�• Polarimetric entropy derived from HP and conventionalpolarimetric measurements show similar performance todiscriminate among slick-free, weak-damping slick-cov-ered and strong-damping slick-covered sea surfaces.

All the above items are scientically and operationally of in-terest since they provide a systematic analysis of SAR oil slickobservation performance via HP features.

ACKNOWLEDGMENTThe authors would like to thank the Japan Aerospace Explo-

ration Agency (JAXA) for providing the ALOS data used in thisstudy. RADARSAT-2 SAR data were provided by the CanadianSpace Agency under the Science and Operational ApplicationsResearch (SOAR) project 6769.

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Ferdinando Nunziata (S�’03�–M�’12�–SM�’13) wasborn in Italy in 1982. He received the B.Sc. andM.Sc. degrees (summa cum laude) in telecommuni-cations engineering and the Ph.D. degree (curriculumelectromagnetic elds) from the Università degliStudi di Napoli �“Parthenope,�” Napoli, Italy, in 2003,2005, and 2008, respectively.Since 2010, he has been an Assistant Professor

in Electromagnetic Fields with the Università degliStudi di Napoli �“Parthenope.�” Since 2013 he hasbeen guest professor at Shanghai Ocean University

(SHOU), Shanghai, China. His main research interests deal with appliedelectromagnetics, including electromagnetic modeling, single- and multipolar-ization sea surface scattering, radar polarimetry, synthetic aperture radar sea oilslick and metallic target monitoring, spatial resolution enhancement techniques,

and the Global Navigation Satellite System�—Reectometry (GNSS�–R). He isthe author/coauthor of more than 30 peer-reviewed journal papers.Dr. Nunziata was the recipient of the 2003 IEEE GRS South Italy Chapter

Best Remote Sensing Thesis Award, the 2009 Sebetia-Ter International Awardfor his research activities in remote sensing, and the 2012 Latmiral Prize, pro-vided by the Italian society of Electromagnetics (SIEm). He was/is in the Orga-nizing Committee member of the 2008, 2010, 2012, and 2014 IEEE Graduateof Last Decade (GOLD) Remote Sensing Conferences at the European SpaceAgency, Frascati, Italy at the Italian Naval Academy, Livorno, Italy, at the Na-tional Research Council, Rome, Italy, and in Berlin, Germany, respectively. Heserved as a Session Chair at the 2008 and 2012 IEEE International Geoscienceand Remote Sensing Symposia, held in Boston, MA, USA and in Munich, Ger-many, respectively. He is the GOLD representative to the Geoscience and Re-mote Sensing Society (GRSS) AdCom and to the IEEE Italy Section.

Maurizio Migliaccio (M�’91�–SM�’00) was bornin Naples, Italy, in 1962. He received the Laureadegree (with honors) in electronic engineering fromthe Università degli Studi di Napoli �“Federico II,�”Naples, Italy, in 1987.He was a Visiting Scientist with the German

Aerospace Center (DLR), Oberpfaffenhofen,Germany. He is currently a Full Professor of Electro-magnetics with the Università degli Studi di Napoli�“Parthenope,�” Naples, Italy. He has also lectured inthe United States, Spain, Germany, and Italy. He has

also authored or coauthored more than 250 papers on applied electromagnetics.Dr. Migliaccio was the recipient of the IEEEGeoscience and Remote Sensing

Society (GRSS) Chapter Excellence Award in 2007 and the IEEE GRSS Let-ters Prize Paper Award in 2009. He was also the Chapter Chair of IEEE GRSS.He was the European Union Secretary of the COST 243 Action. He was theIEEE Italy Section Graduate of Last Decade (GOLD) delegate. He was alsothe General Chairman of the 2008, 2010, and 2012 IEEE Graduate of LastDecade (GOLD) Remote Sensing Conferences at the European Space Agency(ESA), Frascati, Italy at the Italian Naval Academy, Livorno, Italy and at theNational Research Council, Rome, Italy, respectively. He was a member of theItalian Space Agency (ASI) Scientic Board. He is a national delegate of theSMOS�–MODE Cost Action. He is a member of the ESA PB�–EO, the ScienticBoard of the Indian Journal of Radio and Space Physics and the SpaceMag.

Xiaofeng Li (SM�’11) received the B.S. degreein optical engineering from Zhejiang University,Hangzhou, China, in 1985, the M.S. degree inphysical oceanography from The First Institute ofOceanography (FIO), State Oceanic Administration,Qingdao, China, in 1992, and the Ph.D. degree inphysical oceanography from North Carolina StateUniversity, Raleigh, NC, USA, in 1997. During hisM.S. program, he completed the course work at theDepartment of Physics, University of Science andTechnology of China, Hefei, China.

From 1985 to 1992, he studied and worked at FIO. Since 1997, he hasbeen with the National Environmental Satellite, Data, and Information Service(NESDIS), National Oceanic and Atmospheric Administration (NOAA), CampSprings, MD, USA. His research interests include remote sensing observationand theoretical/numerical model studies of various types of oceanic andatmospheric phenomena, image processing, ocean surface oil spill and targetdetection with multipolarization synthetic aperture radar, and sea surfacetemperature algorithm development. He is also involved in developing manyoperational satellite ocean remote sensing products at NESDIS.

Sea Oil Slick Observation Using Hybrid-Polarity SAR Architecture

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