On the Mueller Scattering Matrix for SAR Sea Oil Slick Observation

Nunziata, Ferdinando; Gambardella, A.; Migliaccio, M.

doi:10.1109/lgrs.2008.2003127

Cited by 95 publications

(81 citation statements)

References 13 publications

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“…(A5) 0.3708242 c 4 −0.040590 c 5 0.404678 c 6 0.188397 c 7 −0.027262 c 8 0.064650 c 9 0.054500 c 10 0.086350 c 11 0.055100 c 12 −0.058450 c 13 −0.096100 c 14 0.412754 c 15 0.121785 c 16 −0.024333 c 17 0.072163 c 18 −0.062954 c 19 0.015958 c 20 −0.069514 c 21 −0.062945 c 22 0.035538 c 23 0.023049 c 24 0.074654 c 25 −0.014713…”

Section: Appendixmentioning

confidence: 99%

“…For instance, Melsheimer et al [8] derived the rain rate using the phase differences in cross-and co-polarization data of SIR-C. Migliaccio et al [10] presented a promising study for detecting oil spills by combining the constant false-alarm rate (CFAR) filter and the polarimetric parameters of entropy, alpha and anisotropy of SIR-C data. Using the same dataset, Nunziata et al [11] demonstrated that the Muller matrix is capable of observing oil spills and distinguishing features that look similar.…”

Section: Introductionmentioning

confidence: 99%

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Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

Ren

Zhou

2015

Remote Sensing

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Abstract:The Geophysical Model Function (GMF) XMOD1 provides a linear algorithm for sea surface wind field retrievals for the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR). However, the relationship between the normalized radar cross section (NRCS) and the sea surface wind speed, wind direction and incidence angles is non-linear. Therefore, in this paper, XMOD1 is revisited using the full dataset of X-SAR acquired over the ocean. We analyze the detailed relationship between the X-SAR NRCS, incidence angle and sea surface wind speed. Based on the C-band GMF CMOD_IFR2, an updated empirical retrieval model of the sea surface wind field called SIRX-MOD is derived. In situ buoy measurements and the scatterometer data of ERS-1/SCAT are used to validate the retrieved sea surface wind speeds from the X-SAR data with SIRX-MOD, which respectively yield biases of 0.13 m/s and 0.16 m/s and root mean square (RMS) errors of 1.83 m/s and 1.63 m/s.

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Section: Appendixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

Ren

Zhou

2015

Remote Sensing

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“…A completely different scattering behaviour applies when dealing with strong-damping oil-covered sea surface, i.e. a non-Bragg scattering mechanism applies (Migliaccio, Gambardella, and Tranfaglia 2007;Nunziata, Gambardella, and Migliaccio 2008;Nunziata, Migliaccio, and Gambardella 2011). Hence, following this theoretical rationale, a set of polarimetric features is defined and used to measure the departure from Bragg scattering.…”

Section: Introductionmentioning

confidence: 99%

SAR polarimetry for sea oil slick observation

Migliaccio

Nunziata

Buono

2015

International Journal of Remote Sensing

130

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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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“…With the advent of polarimetric SARs, new, effective, and automatic physical approaches have been conceived to locate and monitor oil spills [Gade et al, 1998;Migliaccio et al, 2011Migliaccio et al, , 2009aMigliaccio et al, , 2009bNunziata et al, 2011Nunziata et al, , 2010Nunziata et al, , 2008Velotto et al, 2011;Zhang et al, 2011]. These new approaches exploit the correlation characteristic between and among polarimetric signals when crude oil at sea is observed.…”

Section: Polarimetric Sar Observationmentioning

confidence: 99%

“…This behavior has been successfully exploited in the development of simple and effective filtering techniques to observe oil at sea in dual-polarimetric SAR data [Migliaccio et al, , 2009a[Migliaccio et al, , 2009bVelotto et al, 2011]. When a fully polarimetric SAR is available, the hv or vh polarimetric signals can be used along with the hh and vv channels to develop techniques that are able to provide a simple and logical true or false output that limits uncertainties in interpretation [Migliaccio et al, , 2009bNunziata et al, 2011Nunziata et al, , 2008Zhang et al, 2011].…”

Section: Polarimetric Sar Observationmentioning

confidence: 99%

Polarimetric synthetic aperture radar utilized to track oil spills

et al. 2012

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The continued demand for crude oil and related petroleum products along with the resulting upward spiral of the market price of oil have forced oil exploration and production companies to seek out new reserves farther offshore and in deeper waters. The United States is among the top five nations globally in terms of estimated offshore oil reserves and petroleum production. Yet deepwater drilling to extract these reserves is a major engineering challenge for oil companies. Moreover, such drilling activity also comes with a significant environmental risk, and the extremely high pressures associated with deepwater oil wells mean that the mitigation of accidental releases from a deepwater spill is truly a challenging endeavor.

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On the Mueller Scattering Matrix for SAR Sea Oil Slick Observation

Cited by 95 publications

References 13 publications

Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

SAR polarimetry for sea oil slick observation

Polarimetric synthetic aperture radar utilized to track oil spills

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