Attilio Gambardella

SAR Polarimetry to Observe Oil Spills

A study on sea oil spill observation by means of polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on the use of a polarimetric constant false alarm rate filter to detect dark patches over SAR images. Then, the target decomposition theorem is exploited to distinguish oil spills and look-alikes. Experiments are conducted on polarimetric SAR data acquired during the SIR-C/X-SAR mission on October 1994. The data were processed and calibrated at the Jet Propulsion Laboratory, National Aeronautics and Space Administration. Results show that the new polarimetric approach is able to assist classification

On the co-polarized phase difference for oil spill observation

In this study dual‐polarized synthetic aperture radar (SAR) measurements were used to enhance oil spill observation. The co‐polarized phase difference (CPD) was modelled and used to characterize the scattering return from oil spills and biogenic slicks. The model predicts, under low to moderate wind conditions, a larger CPD standard deviation (σ) for oil with respect to the sea, while for biogenic slicks a σ value similar to that for the sea is obtained. Experiments accomplished with multilook complex (MLC) C‐ and L‐band SAR data show that the model predictions are confirmed and that the C‐band is, as expected, to be preferred to the L‐band.

On the Mueller Scattering Matrix for SAR Sea Oil Slick Observation

In this letter, a fully polarimetric electromagnetic model for sea surface Mueller matrix is exploited to characterize the scattering from oil and biogenic slicks, under low-to-moderate wind conditions. The model predicts a completely different scattering mechanism for oil-covered and oil-free sea surface, while biogenic slicks are indistinguishable from sea surface in terms of polarimetric scattering. Following this theoretical rationale, a simple and very effective filtering technique is proposed for synthetic aperture radar (SAR) sea oil slick observation. Experiments, accomplished over C-band multilook complex SIR-C/X-SAR data, show the effectiveness of the proposed model and the capabilities of the filter to both observe oil slicks and distinguish them from biogenic look-alikes.

The PALSAR Polarimetric Mode for Sea Oil Slick Observation

A study on sea oil slick observation by means of L-band polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on different sea surface scattering mechanism expected with and without surface slicks. Polarimetric measurements are processed by means of a simple and very effective filtering technique which is electromagnetically based on the Mueller scattering matrix. Moreover, some polarimetric features, evaluated on both slick-free and slick-covered sea surfaces, are analyzed for confirming the filter output. Experiments are accomplished on the polarimetric SAR data acquired by the Phased Array-type L-band Synthetic Aperture Radar (PALSAR) sensor, mounted on board of the Advanced Land Observing Satellite (ALOS), and are relevant to oil slick, due to a tank accident, and look-alikes. Results demonstrate for the first time that L-band polarimetric SAR measurements are useful for oil slick observation purposes and witness the capability of the ALOS PALSAR data for such application.

On the Superresolution of Microwave Scanning Radiometer Measurements

Microwave radiometer measurements are exploited to extract important geophysical information. Although it is beneficial to merge different frequency channels, it requires extra effort to refer all measurements to a common spatial resolution. Therefore, the capability to enhance the spatial resolution of a single channel is of special interest. In this study, a new numerical procedure to get superresolution microwave scanning radiometer measurements is presented. The approach is physically based on the occurrence of multiple partially correlated measurements. Mathematically, the approach is equivalent to a linear inversion problem, and its solution is pursued by means of a superresolution numerical procedure based on the Tikhonov regularization method. A set of numerical examples illustrates the results of the study in which hypothetical scanning microwave radiometer sensor configuration and reference test cases have been considered.

A Physically Consistent Speckle Model for Marine SLC SAR Images

A new physically based speckle model for marine single-look complex (SLC) synthetic aperture radar (SAR) images is here presented and investigated. The model allows using full-resolution SAR images instead of multilook SAR images, in which, at the expense of a coarser spatial resolution, the speckle is mitigated. The model is based on the three-parameters generalized-K (GK) probability density function (pdf). GK pdf is a suitable physically-based speckle model for marine SAR images ensuring a continuous and physically consistent transition among different scattering scenarios. This speckle model embodies Rayleigh, K, and Rice scattering scenes which are typical of marine scenes. The use of the three parameters, related to the GK pdf ones, is able to highlight the presence of both low backscattering areas and areas in which a small dominant scatterer is present. This is operationally interesting in SAR oil spill detection procedures.

Microwave radiometer spatial resolution enhancement

Scanning radiometer data processing can allow enhancing the limited intrinsic spatial resolution. This is important for data fusion. Mathematically, the problem to be solved is an inverse ill-posed problem. In this paper we compare the classical Backus-Gilbert inversion method with the truncated singular value decomposition (TSVD) one. A one-dimensional intercomparison is accomplished using an hypothetical sensor configuration. Results show the superiority of TSVD inversion method.

One-class classification for oil spill detection

SAR oil spill classification is a challenging topic, which is tackled by semi-empirical ad hoc approaches supported by very qualified experts. In all cases, the feature space is empirically defined, and two-class classification approaches are used. Although this approach allows achieving acceptable operational results, there is still room for improving both the comprehension of the physical phenomenon and the performance of classification techniques. In this paper, we propose a novel approach to oil-spill classification based on the paradigm of one-class classification. A classifier is trained using only examples of oil spills, instead of using oil spills and look-alikes, as in two-class approaches. Further, since the feature space is empirically defined, we also propose an objective technique to select the most powerful one that is suited for the oil-spill detection task at hand. Results on two case study datasets are reported to validate the proposed approach.

A Physical Full-Resolution SAR Ship Detection Filter

Synthetic aperture radar (SAR) ship detection is an important application in the context of environment and security monitoring. It allows monitoring traffic, fisheries, and associating ships with oil discharge over wide areas with high spatial resolution almost independently from weather conditions and both day and night time. Since full-resolution SAR images are heavily affected by the presence of speckle, ship detection algorithms generally employ speckle reduced SAR images at the expense of a degradation of the spatial resolution. A new physical approach, which considers ships as dominant scatterers and, therefore, responsible for a strong and coherent backscattered signal, is here proposed. Based on this rationale, a new simple and very effective filtering technique, which is able to process full-resolution SAR images, has been conceived and implemented. Experiments, accomplished over C-band European Remote Sensing satellite (ERS) 1/2 single-look complex SAR images, show the effectiveness of the proposed approach.

A unitary Mueller-based view of polarimetric SAR oil slick observation

Synthetic aperture radar (SAR) oil slick observation is a topic of great applicative relevance which has been physically recast by a set of new polarimetric approaches that exploit the departure from Bragg scattering. In this article, under a unitary Mueller-based view, all the approaches are revisited and reformulated in terms of Mueller matrix elements. This new view is of theoretical and applicative relevance because it allows us to ‘unify’ the output parameters in the same range and, therefore, makes possible a fair ranking of these approaches.