Marine added-value products using RADARSAT-2 fine quad-polarization

Migliaccio, Maurizio; Nunziata, Ferdinando; Montuori, Antonio; Brown, Carl E.

doi:10.5589/m11-054

Cited by 38 publications

(15 citation statements)

References 15 publications

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“…All those polarimetric features have been widely and successfully exploited for sea oil slick monitoring: the target entropy H in (Migliaccio, Gambardella, and Tranfaglia 2007;Nunziata, Gambardella, and Migliaccio 2012;Migliaccio, Nunziata, Montuori, et al 2012), the anisotropy coefficient A and the mean scattering angle α in (Zhang et al 2011; and the geometric mean or covariance scaling factor ν in (Zhang et al 2011;.…”

Section: Quad-polarimetric Featuresmentioning

confidence: 99%

“…The vv-polarized intensity image relevant to the Radarsat-2 acquisition (ID: PDS_01141690) collected on 15 May 2010 off the Louisiana Coasts, in the Gulf of Mexico, is shown in Figure 1(c). The imaged area covers a well-known oil field where both metallic targets and oil slicks are present (Migliaccio, Nunziata, Montuori, et al 2012). In Figure 1 …”

Section: Data Setsmentioning

confidence: 99%

“…In Table 1, the progress of polarimetric spaceborne SAR architectures is summarized, from the first fully polarimetric SAR sensor, Spaceborne Imaging Radar (SIR) C/X, launched by National Aeronautics and Space Administration (NASA) in 1994 and by now dismissed, to the near future polarimetric satellite missions equipped with CP SAR configurations already planned for next years as RCM and the National Space Activities Commission (CONAE) Spanish for Argentine Microwaves Observation Satellite (SAOCOM), passing through the actually operational Risat-1 and ALOS PALSAR-2. In the literature, spaceborne fully/dual-polarized L-, C-, and X-band SAR data have been exploited for sea oil slick monitoring Migliaccio, Nunziata, Montuori, et al 2012;Zhang et al 2011;Velotto et al 2011;Kudryavtsev et al 2013;Matkan, Hajeb, and Azarakhsh 2014;. Different polarimetric techniques have been successfully applied to detect ship-based oil spills, to monitor and support remediation activities in the case of large accidental oil spills, and to observe natural oil seeps.…”

Section: Introductionmentioning

confidence: 99%

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SAR polarimetry for sea oil slick observation

Migliaccio

Nunziata

Buono

2015

International Journal of Remote Sensing

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131

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In this article, a review of polarimetric synthetic aperture radar (SAR) methods for sea oil slick observation is presented. Marine oil pollution monitoring is a topic of great applicative and scientific relevance. In this framework, the use of remotely sensed measurements is of special interest and, in particular, the SAR because of its almost all-weather and all-day imaging capability at fine spatial resolution is the most effective tool. Conventional single-polarization SAR oil spill monitoring techniques are limited in their capability to detect oil slicks since they strongly rely on suitable thresholds, training samples, and ancillary information. Hence, an expert image analyst is due. The launch of a number of polarimetric SAR missions, along with the understanding of the peculiar physical mechanisms governing the scattering by an oil slick, led to a new paradigm (known as physical processing) that fostered a set of polarimetric algorithms particularly robust and efficient. Hence, suitable polarimetric models that exploit the departure from the slick-free sea Bragg scattering have been developed to effectively address oil slick monitoring. A set of polarimetric features extracted following such electromagnetic models have been proved to be reliable for oil slick monitoring. Polarimetric SAR observations led to a significant improvement in sea oil slick observation since they allow distinguishing oil slicks from a broad class of lookalikes in an unsupervised way. In addition, deeper information on the damping properties of the pollutant can be also inferred, which is of paramount importance for remediation purposes. Such physical processing has been demonstrated to be robust at variance of microwave carrier frequency, e.g. L-, C-, and X-band, and suitable to be exploited to extract information by dual-polarized, full-polarized, and compact modes. All these make such a physical approach of operational interest since it is able to exploit a larger set of SAR measurements building up a virtual constellation. In this review all these are detailed.

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Section: Quad-polarimetric Featuresmentioning

confidence: 99%

Section: Data Setsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SAR polarimetry for sea oil slick observation

Migliaccio

Nunziata

Buono

2015

International Journal of Remote Sensing

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131

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“…Introduction Ship detection, while having an expansive application prospect in the area of marine traffic, ocean fishing, and surveillance, is one of the most important aspects of ocean applications based on synthetic aperture radar (SAR) imagery (Ferrara et al 2011;Wang, Liao, and Li 2008). With the development of radar imaging technology and the implementation of polarimetric SAR (PolSAR) systems, ship detection in PolSAR imagery has become an active research topic (Brusch et al 2011;Crisp 2004;Marino and Walker 2011;Migliaccio et al 2011Migliaccio et al , 2012Nunziata, Migliaccio, and Brown 2012). Compared with single-channel SAR imagery, PolSAR data describe the target's scattering mechanism more comprehensively.…”

Section: Feature Selection and Weighted Svm Classifier-based Ship Detmentioning

confidence: 98%

Feature selection and weighted SVM classifier-based ship detection in PolSAR imagery

Xing

Zou

et al. 2013

International Journal of Remote Sensing

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Target decomposition is an important method for ship detection in polarimetric synthetic aperture radar (SAR) imagery. Parameters such as the polarization entropy and alpha angle deduced from the coherency matrix eigenvalue decomposition capture the differences between the target and background from different views separately. However, under the conditions of a relatively high resolution and a rough sea, the contrast between ship and sea reduces in the aforementioned space. Based on the analyses of target decomposition theory and the target's scattering mechanism, multi-polarization parameters can be used to characterize different scattering behaviours of the ship target and sea clutter. Moreover, each parameter has its own diverse significance in the practical detection problem. This article proposes a feature selection and weighted support vector machine (FSWSVM) classifier-based algorithm to detect ships in polarimetric SAR (PolSAR) imagery. First, the method constructs a feature vector that consists of multi-polarization parameters. Then, different polarization parameters are refined and weighted according to their significance in the support vector machine (SVM) classifier. Finally, ships are classified from the sea background and other false alarms by the classifier. The validation results on National Aeronautics and Space Administration/Jet Propulsion Laboratory (NASA/JPL) airborne synthetic aperture radar (AIRSAR) and Radarsat-2 quad polarimetric data illustrate that the method detects ship targets more precisely and reduces false alarms effectively.

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“…Today, there is a general consensus that the extra-information provided by the transmit/receive antenna polarizations increases the performance of target detection algorithms. New physically based polarimetric approaches have been developed to observe metallic targets at sea [3]- [11], supported also by new high-performances polarimetric SARs, e.g., the ones operated onboard the ALOS, RADARSAT-2, TerraSAR-X, and COSMO-SkyMed (CSK) missions. In [3], the coherent target decomposition (CTD) is enhanced to extend its range of applicability, and the symmetric scattering characterization method (SSCM) is introduced to better exploit the information provided by the symmetric scattering component in the frame of coherent scattering.…”

Section: Introductionmentioning

confidence: 99%

On the COSMO-SkyMed PingPong Mode to Observe Metallic Targets at Sea

Nunziata

Migliaccio

2013

IEEE J. Oceanic Eng.

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A dual-polarimetric model to exploit X-band COSMO-SkyMed (CSK) dual-polarimetric PingPong mode synthetic aperture radar (SAR) data for metallic target observation purposes is first developed. The model relates the correlation between the copolarized channels, in case of sea surface with and without metallic targets, to the time offset between bursts related to the HH and VV polarimetric channels. Following this theoretical rationale, a constant false alarm rate (CFAR) approach is implemented to first exploit CSK PingPong full-resolution SAR data for target observation purposes. Experiments undertaken over a large data set of COSMO-SkyMed single look complex slant (SCS) PingPong HH/VV SAR data demonstrate the physical soundness of the approach and its effectiveness from an operational viewpoint. A whole CSK SAR scene is processed in about 10 s. Furthermore, the dual-polarization approach is also compared with a conventional single-polarization CFAR one and it is shown to perform best.

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Marine added-value products using RADARSAT-2 fine quad-polarization

Cited by 38 publications

References 15 publications

SAR polarimetry for sea oil slick observation

SAR polarimetry for sea oil slick observation

Feature selection and weighted SVM classifier-based ship detection in PolSAR imagery

On the COSMO-SkyMed PingPong Mode to Observe Metallic Targets at Sea

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