In this study, a novel approach is proposed to extract dynamic information about Terra Nova Bay (TNB) polynya, Antarctica, using a single Synthetic Aperture Radar (SAR) imagery collected by the Sentinel-1 mission. The proposed approach is based on a joint scattering/morphological and spectral analysis of key features, namely the sea ice streaks, that characterise polynyas. A set of single- and dual-polarimetric SAR Sentinel-1 measurements collected over the open TNB polynya under different growing and closing phases are used for the experimental analysis, which is assisted by ancillary optical and radiometer satellite products. Experimental results demonstrate the ability of co-polarised backscattering to identify the open polynya growing and closing phases using a single SAR scene. This suggests using SAR measurements to fill the temporal and spatial gaps arising from the monitoring of the harsh TNB polynya environment.

Green macroalgae (GMA) are prominently visible as distinctive bright mats on Synthetic Aperture Radar (SAR) imagery that are frequently used to complement conventional optical observations for extracting GMA distribution at sea. However, the mechanisms ruling the interaction between the microwaves and the GMA are not well understood. This study aims to address this gap by systematically analyzing C-band backscattering from GMA-covered sea surfaces from a physical perspective using dual-polarized Sentinel-1 SAR imagery combined with a three-layer description of the GMA-covered sea surface. Firstly, the dual-polarized normalized radar cross-section (NRCS) is analyzed showing that the co-polarized backscatter is always above the system noise while this is not the case for the cross-polarized backscatter that is frequently noisy. Then, polarimetric descriptors are adopted to shed light on the GMA backscatter mechanisms. The degree of polarization (DoP) is evaluated to demonstrate that the electromagnetic (EM) wave backscattered from the GMA is almost fully polarized, indicating a negligible depolarized component. Finally, the polarization ellipse associated to the EM wave backscattered from the GMA is analyzed showing the GMA call for a linearly-polarized (almost vertically oriented) backscattered EM wave. This finding suggests a scattering mechanism dominated by single reflection and a residual multiple reflection component within the wet-GMA layer of the three-layer schematic model. The analysis is extended to several imagery collected under different green tide stages showing that the above-mentioned findings always apply.

This study analyses the C-band multi-polarization backscattering properties of offshore wind farms. The data set includes a large time series of satellite synthetic aperture radar imagery collected by the European Space Agency Copernicus mission Sentinel-1. As a test site, the Robin Rigg offshore wind farm located in the Solway Firth, (UK) is selected. The aim of this study is to extract the multi-polarisation normalized radar cross section and reflection symmetry information over selected wind turbines and a reference target-free sea surface area to analyze the corresponding backscattering features over time. Preliminary results suggest that the detectability of wind turbines is strictly related to the considered multipolarization parameters, for which co-polarized backscattering dominates over the cross-polarized one. In addition, wind turbines are characterized by a correlation between co- and cross-polarized channels larger than the surrounding sea surface, which satisfies the reflection symmetry property.

This study focuses on the capability of extracting the waterline in different cases using quad-polarimetric (QP) X-band Synthetic Aperture Radar (SAR) measurements. A baseline unsupervised waterline extraction scheme is applied which is feed with single-, dual- and quad-polarimetric features to assess the role of polarimetric information. Two different scenarios are accounted for: i) a sandy and gently coastal profile; ii) an inland steep water bodies. The study areas are identified in the Ionian coast of Basilicata region, south of Italy, where QP SAR images collected by the Cosmo-SkyMed Second Generation (CSG) Italian satellite constellation are collected over the Metaponto Plain and the San Giuliano dammed artifical lake, respectively. Preliminary results obtained from the inland water body suggest that full-polarimetric CSG SAR data have potential to be used to perform unsupervised waterline extraction, even though the specific water conditions and coastal morphology must be carefully accounted for.

In this study, the potential of electromagnetic scattering models to retrieve quantitative parameters of sea oil spills is investigated using an artificial intelligence (AI)-based approach. The backscattering coefficient of a slick-covered sea surface is predicted using the advanced integral equation model augmented with the model of local balance (MLB), an effective dielectric constant model, and a composite medium model to include the effect of an oil slick. Damping ratios (DRs), predicted for different oil parameters (namely, the oil thickness and seawater volume fraction), are used to train and test a four-layer neural network. Once successfully tested, the neural network is applied to an uninhabited aerial vehicle synthetic aperture radar (UAVSAR) image collected during the DeepWater Horizon (DWH) oil spill accident to retrieve the oil slick thickness and volume fraction of seawater in the oil layer. The inversion results show that the thicker (i.e., 2–4 mm) emulsions are located in the south and west of the slick and they are surrounded by thinner (i.e., < 1 mm) oil films. In addition, the seawater volume fraction in the oil slick is found to be about 20%–30%. Results are contrasted with optical data and previous studies of the same accidental oil spill, showing qualitatively good agreement.

In this study, a scattering analysis of wind turbines is performed using a multi-frequency and multi-polarisation synthetic aperture radar dataset. The latter includes L-, C- and X-band synthetic aperture radar imagery collected by Alos PalSAR-2, Sentinel-1 and PAZ, respectively. Multi-polarization normalized radar cross sections and reflecion symmetry are considered to characterize the backscattering properties of the Robin Rigg offshore wind farm (Solway Firth, UK) turbines, whose features are evaluated with reference to a target-free surrounding sea surface. The experimental results show that the detectability of the wind turbines is severely influenced by the incident wavelength, with the reflection symmetry being a robust and effective parameter to characterize wind turbines. Co-polarized backscattering is always larger than the corresponding cross-polarized one at that HH-polarized backscattering is larger at L-band rather than at X-band, while the C-band VV-polarized backscattering is the lowest. Considering cross-polarized channel, wind turbines call for the largest (lowest) backscattering at X-band (C-band). Results also show that wind turbines are characterized by a correlation between co- and cross-polarized channels much larger than the surrounding sea surface, which satisfies reflection symmetry. In particular, the HH-HV correlation is, on average, larger at X-rather than L-band, while the C-band VV-VH correlation is much lower.

In this study, the L-band polarimetric scattering of a fishing trawler is investigated with respect to the synthetic aperture radar incidence angle. This unique opportunity is explored using a time series of airborne uninhabited aerial vehicle synthetic aperture radar imagery where the same small fishing trawler is observed under a broad range of incidence angles, spanning from about 35° up to 55°. The degree of polarization and its polarization signature are extracted from the synthetic aperture radar data set to evaluate the L-band polarimetric scattering of the ship target under analysis, with emphasis on the changes in the ship scattering associated with the polarized part of the backscattered signal. Furthermore, changes in the dynamic of the degree of polarisation signature over the fishing trawler and a reference target-free sea surface area are analyzed quantitatively, showing that the polarized component of the L-band signal scattered off sea and ship is significantly sensitive to the acquisition geometry, i. e., the synthetic aperture radar incidence angle.

This study is to analyze the multi-polarization backscattering from intertidal areas using polarimetric synthetic aperture radar imagery collected by the X-band Cosmo-SkyMed Second Generation satellite mission. In this study, we focus on the Solway Firth (Scotland) area that includes different habitats as wetland, salt marshes, sand dunes, and mudflats. In particular, mudflats presents a large variability of normalized radar cross section that may limit significantly the classification performance of intensity-based approaches. Within this context, for the first time, we exploit full-polarimetric Cosmo-SkyMed Second Generation imagery collected in StripMap mode.

In this paper, a multi-frequency analysis of onion crop backscattering is undertaken to monitor crop phenology. Time changes of onion backscattering from C-band Sentinel-1 and X-band COSMO-SkyMed synthetic aperture radar imagery are investigated to infer information on the growth stages of onions. The test site is located in the South of Italy, Avellino province, where a sensors’ network on the ground is in place that continuously monitor soil and atmospheric parameters as temperature, moisture, wind field, etc. The test site is also equipped with an optical camera that provides real time pictures of the onion field. In this study, co-polarized (VV at C-band and HH at X-band) and cross-polarized (VH at C-band) backscattering coefficients are analyzed over the onion crop together with ancillary independent ground information. Experimental results show that the considered features have good sensitivity to the onion growth and allow identify four phenologial stages during the time span investigated in this study.

This study is to present the lesson learned during the activities related to the Italian Space Agency (ASI) funded APPLICAVEMARS project which aims at estimating sea surface wind field from L-, C- and X-band Synthetic Aperture Radar (SAR) imagery. The paper focuses on the X-band results and it describes a new approach to estimate ancillary wind direction info from the SAR image itself using neural networks.

In this study, the polarimetric scattering of a ship and the surrounding sea is analysed at multiple incidence angles using fully polarimetric L-band Synthetic Aperture Radar (SAR) data. The behaviour of polarised and unpolarised backscatter is analysed using the degree of polarisation, the signature of the degree of polarisation, and the pedestal height. Experimental results show that, although the unpolarised backscattered power increases monotonically versus the incidence angle for both target and sea, the two scenarios call for a distinctive polarimetric behaviours. The polarised component in the backscattered signal is demonstrated to be the main source of variability of the target-to-clutter ratio (TCR) against the incidence angle.

In this study, the multi-polarization L-band scattering mechanisms of internal waves are investigated. Internal waves represent key geophysical factors for sea-air heat ex-change, playing an important role on the evolution of marine ecosystems. Hence, a better understanding of internal waves microwave scattering mechanisms can support the devel-opment of advanced tools based on polarimetric synthetic aperture radar imagery. The latter can be exploited to miti-gate the impact internal waves may have on offshore drilling operations and aquaculture. In this study, the analysis is performed using full-polarimetric L-band synthetic aperture radar images of internal waves ob-served under different radar imaging parameters and sea state. The analysis is also supported by ancillary information from external independent sources. Experiments show that the co-polarized backscattering of internal waves is remarkably impacted by non-polarized scattering mechanisms, with the wave crest signatures being more affected than the troughs.

In this study, a multi-frequency analysis on the polarimetric scattering of harsh coastal environments is addressed. The polarimetric properties of different scattering scenarios including grasslands and agricultural crops over land, mudflats and sea water are analyzed using the polarization signatures and the correlation between the co-polarized channels. To this purpose, C- and X-band quad-polarimetric synthetic aperture radar satellite measurements are collected over the Solway Firth, along the western coastal area at the borders between England and Scotland. The Solway Firth coastal area represents a meaningful showcase since it consists of a mixture of harsh environments resulting from different meteo-marine conditions and natural/anthropogenic coastal processes, e.g., erosion, tides, sedimentation, storms, sea currents. Preliminary results obtained at C-band show that polarimetric analysis tools allow improving the understanding of natural and anthropogenic processes in harsh coastal environments that may support the development of advanced and robust scattering-based algorithms for coastal management purposes.

In this paper, preliminary results obtained within the framework of the Italian Space Agency-funded APPLICAVEMARS project are presented. The project aims at estimating sea surface wind field from L-, C- and X-band Synthetic Aperture Radar (SAR) imagery. In particular, the key element is the adaptation/improvement of geophysical model functions to transform the microwave reflectivity map into an added-value product, i.e., a wind map characterized by a spatial resolution much finer than the one obtainable from scatterometer measurements. First experimental results related to C-band Sentinel-1 SAR imagery are presented.

In this study, the bistatic radar scattering coefficients related to an oil-covered sea surface are predicted by modeling both the oil damping effect on surface roughness–through the advanced integral equation method–and the oil modification on the dielectric properties of the scattering surface. The bistatic scattering is analyzed in the whole upper scattering space under different radar frequencies, incidence angles, wind speeds, and oil thicknesses. Numerical predictions show that the scattering energy of an oil-covered sea surface is generally higher in the forward scattering zone than that in the backward one. In addition, the oil damping effect is the main mechanism ruling the scattering behavior in the backward region. The information related to the bistatic scattering geometry is also explored to retrieve oil thickness, representing one of the key parameters for radar-based marine oil pollution observation. A new index is proposed to quantify the sensitivity of bistatic scattering coefficients to oil thickness in different cases: single-polarization features, dual co-polarization features, namely, the polarization ratio (PR) and the normalized polarization difference index (NPDI), and dual-angular scattering features. Numerical results show that the bistatic scattering coefficients result in an enhanced sensitivity to oil thickness with respect to the monostatic case. The single HH-polarized scattering coefficients show better oil thickness sensitivity in the backward region, while the VV-polarized ones are more sensitive to oil thickness in the forward region. The combination of dual-polarized scattering coefficients significantly improves the oil thickness sensitivity compared to single-polarization radar observations, especially in the forward region. PR outperforms NPDI, even though the latter can suppress the effect of wind speed. The combination of dual-angular observations can significantly increase its sensitivity of oil thickness in the backward region but at the expense of reduced sensitivity in the forward region.

Oils floating on the sea surface can be observed as “dark” patches on radar images since the backscattered signals from the contaminated area are reduced in two dominant ways. First, oil slicks could damp short gravity and capillary waves on the sea surface responsible for backscattering energy. Second, the oil-covered sea surface permittivity decreases significantly if the oil film is sufficiently thick or mixed with seawater, i.e., oil emulsion. In this article, the geometry of the oil-covered sea surface is accounted for by the damping of sea waves, which is described by the model of local balance (MLB) combined with the sea wave spectrum. The radar backscattering is predicted by the advanced integral equation method (AIEM) model. The reflection coefficients are calculated based on a layered-medium model to analyze the impact of oil thickness and emulsions on the radar scattering. Numerical simulations demonstrate that: 1) the sensitivity to oil thickness and water content of the oil spills increases when the radar frequency increases; 2) the backscattering signals exhibit a nonlinear behavior with respect to oil thickness; and 3) high wind speed can generally narrow the difference between the radar backscattering from the clean and oil-covered sea surface, while the incidence angle has little effect. Numerical simulations are then compared with the multifrequency synthetic aperture radar observations acquired during the Gulf of Mexico Deepwater Horizon (DWH) oil spill accident and the 2011 Norwegian Clean Seas Association for Operating Companies (NOFO) oil-on-water exercise. Comparison results show that it is possible to estimate the oil thickness at reasonably good accuracy.

This study investigates the behavior of polarimetric scattering from ships for varying incidence angles using a time series of full-polarimetric Synthetic Aperture Radar (SAR) imagery. The time series of PolSAR imagery consists of L-band airborne UAVSAR overpasses over a moving fishing ship imaged at different incidence angles. The experimental analysis consists of discussing the behavior of multi-polarization backscattering and polarimetric features associated to the ship scattering mechanisms at variance of the incidence angle. Preliminary results show that incidence angle affects both the intensity of the backscattering signals and polSAR features. The experimental analysis consists of discussing the behavior of multi-polarization backscattering and polarimetric features associated to the ship scattering mechanisms at variance of the incidence angle. Preliminary results show that incidence angle affects both the intensity of the backscattering signals and polSAR features.

In this study, a dual-polarization (DP) processing chain is presented to identify burned area in C-band PolSAR imagery and to estimate burn severity. The processing is performed according to a DP change detection scheme that uses a pair of SAR imagery collected before and after the wildfire. Finally, the output is clustered into 3 severity classes. Experimental results obtained processing a Sentinel-1 SAR data set collected over the burned area of Monti Pisani, Italy, confirm the soundness of the proposed approach.

In coastal areas, the wind vector at sea is one of the most important geophysical variable of interest. Wind field information is crucial for navigation, green energy production, fishing, etc. Nonetheless, to obtain distributed and accurate sea wind information in coastal areas is a challenging task that cannot be achieved by buoys, anemometers or satellite sensors as lidars and scatterometers. Hence, in this study, the behavior of sea wind field is analyzed over the selected test site, i. e., the Gulf of Naples (Italy, Mediterranean Sea) using level-2 ocean products obtained by the C-band Synthetic Aperture Radar (SAR) on board of the European Space Agency mission Sentinel-1. The latter are compared with space/time co-located wind vectors obtained by the Weather and Research Forecasting (WRF) model. Preliminary experimental results indicate that there is a fairly good agreement between wind vectors estimated from SAR and the ones predicted by the WRF model. They suggest that a moderate eastern wind blowed over the study area in the considered period.

In this study, the capability of polarimetric Synthetic Aperture Radar (SAR) measurements to monitor harsh coastal areas is addressed. A meaningful showcase is presented that refers to the Scottish Solway Firth (SF) wetlands, an important coastal ecosystem severely affected by extreme weather conditions. Experiments are undertaken on a pair of full-polarimetric (FP) C-band RadarSAT-2 SAR images collected over SF during July and November 2018 in order to both extract the coastal profile and to identify changes in the scattering behavior along the coastal strip. The results demonstrate the soundness of the proposed approach and the role played by FP SAR measurements to effectively support vulnerability and risk assessments in harsh coastal environments.

In this study, the capability of polarimetric Non Local Filters (NLFs) for speckle reduction in POLarimetric Synthetic Aperture Radar (POLSAR) measurements is investigated. Among different POLSAR applications where speckle filtering is a key point, shoreline extraction is here addressed. A C-band Radarsat-2 POLSAR scene is considered where the shoreline extraction procedure proposed in [5] is applied. The effects of different POLSAR speckle filters, including NLFs, are analyzed.

In this paper, a time series of 33 TerraSAR-X copolarized synthetic aperture radar (SAR) imagery collected in Stripmap mode over the Gulf of Mexico in a wide range of incidence angles and sea-state condition is exploited, together with a theoretical framework based on the X-Bragg scattering model, to analyze the effects of noise, angle of incidence, (AOI) and wind speed on the standard deviation of the copolarized phase difference (σΦc) evaluated over sea surface with and without oil slicks. This large data set represents an unprecedented opportunity to analyze, for the first time, the influence of both SAR acquisition and surface parameters on the broadening of the copolarized phase difference probability density function (pdf), pΦc(Φc). Experimental results show that the X-Bragg scattering model, here adopted to predict the sea surface pΦc(Φc), gives an understanding of the increasing trend of σΦcwith respect to AOI. It is shown that the noise significantly contributes to broaden pΦc(Φc) over both slick-free and slick-covered sea surface, while the effects of low-to-moderate wind regimes are negligible. In addition, σΦcexhibits a larger sensitivity to the scene variability, if compared to single-polarization intensity channels, over both slick-free and oil-covered sea surface. This sensitivity is more pronounced at lower AOIs due to the higher noise equivalent sigma zero (NESZ) that affects larger AOIs.

A novel physical paradigm is explored in this paper: synthetic-aperture radar (SAR) ocean speckle is informative. This paper experimentally analyzes the SAR ocean speckle intensity K-distribution model versus sea-surface wind field. It is shown that the normalized intensity moments of the K-distribution measured from actual C-band SAR data well fit the theoretical ones under different wind conditions, i.e., wind regime and relative SAR-wind azimuth direction. In addition, it is observed that the K-distribution shape parameter decreases as wind speed increases. A sensitivity of the K-distribution shape parameter on incidence angle and wind direction is also observed, where the largest variability is experienced at higher incidence angles and under crosswind relative azimuth angle.

In this study, polarimetric synthetic aperture radar (PoISAR)-based classification algorithms are considered to investigate the role played by polarimetric information in the classification process of coastal areas that call for heterogeneous scattering properties. Hence, a multi-frequency PolSAR dataset collected over the study area of the Yellow River delta (China) is exploited to point out benefits and limitations that characterize well-known unsupervised classification schemes. Experimental results show the potential and the drawbacks of the exploitation of multi-frequency and multi-polarization SAR measurements for challenging coastal area classification.

In this paper, a unified framework was applied to derive compact polarimetric Synthetic Aperture Radar (SAR) features under general transmit and linear receive polarization conditions. Following the rationale of polarization signature, the characteristics of features derived by transmission of variant roll angles and ellipticity are analyzed. Statistical distance was proposed to quantitatively measure the performance of these compact polarimetric SAR features on marine oil spill classification. Experiment was conducted on a Radarsat-2 quad-pol SAR scene acquired during a controlled oil-on-water exercise.

In this study, coherent co-polarized synthetic aperture radar (SAR) information is exploited for sea oil seep monitoring purposes. A time series of 33 TerraSAR-X StripMap SAR data, collected over a well-known oil seep in Gulf of Mexico, is exploited to analyze the influence of incidence angle and wind conditions on the co-polarized phase difference (CPD). Furthermore, the benefits of using phase information for oil seep observation are assessed. Experimental results show that: i) incidence angle has a remarkable effect in broadening/shrinking the CPD statistical distribution and, ii) the CPD provides spatial information on the oil seep damping properties.

In this study, multi-polarization synthetic aperture radar (SAR) data collected by the C-band Radarsat-2 SAR mission in Antarctica are exploited to observe the Terra Nova Bay (TNB). The latter represent a complex coastal scenario where open ocean, sea ice, polynyas, ice sheets and tongues are present. Single-polarization (SP) features, including co- and cross-polarized backscattering intensities, and dual-polarimetric (DP) features, including eigenvalue-based decomposition features and the polarization ratio, are used to identify the signatures of the different environments that characterize the TNB and to perform an unsupervised classification. Experimental results, obtained using Markov Random Fields and polarimetric decompositions, show that: i) SP and DP features allow estimating the extent of polynya; ii) DP approach allows inferring useful information on the different scenarios; iii) clear signatures can be identified according to the considered multi-polarization feature set.

In this study, a comprehensive analysis of X-band backseat-tering from sea oil seeps is undertaken exploiting: 1) a two-scale scattering model to predict vv-polarized sea surface backscattering with and without oil slicks under different wind speeds and incidence angles; 2) a large time-series of co-polarized dual-polarimetric Synthetic Aperture Radar imagery collected by the German TerraSAR-X mission over the well-known oil seep related to the Taylor Energy accident occurred in 2004 in the Gulf of Mexico.

In this paper, a comparitive analysis between full-polarimetric (FP) and compact-polarimetric (CP) synthetic aperture radar (SAR) architectures is performed within the frame of sea oil slick observation. Those architectures provide similar results in terms of detection/discrimination capability, but subtle differences apply. The latter are here investigated through an eigen-analysis undertaken using the X-Bragg sea surface scattering model. Predictions based on the theoretical model are verified by experiments undertaken on actual FP SAR measurements, from which CP SAR data are emulated. Results confirm the soundness of the proposed analysis, pointing out that CP SAR achieve performance that tends to that of FP ones, and that the different behavior they exhibit even on slick-free sea surface can be explained by the different eigenvalues of polarimetric observables, i. e., the coherency matrix T and the wave coherency matrix Twfor FP and CP SAR, respectively.

This study proposed a novel method to analyze slick-free and oil covered sea surface backscattering in the special case of Deepwater Horizon (DWH) oil spill accident based on combination of tilted Bragg scattering and volume scattering components. The DWH accident represents a particular and challenging case due to the very large amount of leaked oil that came from the bottom of the ocean. The proposed scattering model consists of first estimate the large scale tilting angle of sea surface Bragg scattering mechanism and then of the retrieval, through its linear relationship with the relative dielectric constant, of oil-insea volume concentration. Finally, Bragg and volume scattering components can be estimated which provide useful information for a better understanding of i) the sea surface status and ii) the weak-damping properties the leaked oil due to purification/emulsification phenomena. The model is tested considering actual UAVSAR L-band fully-polarimetric SAR data.

In this study, polarimetric Synthetic Aperture Radar (pol-SAR) features are derived from full-, dual- and compact-polarimetric SAR measurements and their performance is investigated for sea oil slick observation purposes. Experiments undertaken on a RadarSAT-2 SAR scene collected over well-known oil slicks show that all the polSAR architectures allow correctly emphasizing oil slicks with respect to the surrounding sea. Full-pol and compact-pol SAR architectures allow detecting oil slicks without any adaptive thresholding, the latter is needed when dealing with dual-pol (co-co) SAR measurements. As a matter of fact, the key pitfall of pol-SAR, i.e. its limited swath, can be successfully overcame by compact-polarimetric architecture that, with respect to sea oil slick observation, exhibits performance similar to full-polarimetric SAR.

In this letter, fully polarimetric (FP) and compact polarimetric (CP) synthetic aperture radar (SAR) features are investigated over the sea surface. While exhibiting similar trends, subtle differences are observed and investigated here using a new model-based approach. The model indicates that differences between the FP and CP architectures, and among the CP modes, are due to the difference in mapping between the polarimetric observables and the eigenvalues. This is verified using actual FP SAR data and emulated CP SAR measurements.

In this paper, a theoretical and experimental analysis of polarimetric synthetic aperture radar (SAR) architectures is undertaken for sea oil slick observation purposes. Reference is made to the conventional full-polarimetric (FP) SAR that is here contrasted with new-generation polarimetric SAR architectures, known as compact-polarimetric (CP) SAR. Two CP modes are considered, i.e., the hybrid-polarity and π/4 modes, whose measurements are emulated from actual L- and C-band FP SAR data. Polarimetric sea surface scattering is predicted according to an extended version of the Bragg scattering model (X-Bragg) in order to point out the differences exhibited between FP and CP SAR architectures and among CP SAR modes. Theoretical predictions are then contrasted with experiments undertaken on actual polarimetric SAR data collected over well-known oil slicks and weak-damping surfactants. Results confirm model prediction, showing that differences mainly apply when polarimetric features are estimated over slick-free sea surface using different SAR architectures, with the π/4 mode behaving closer to FP SAR. Although CP SAR architectures measure only a subset of the FP information content, they represent an interesting operational alternative for both detecting oil slicks and discriminating them from weak-damping surfactants.

In this study, the capability of Compact-Polarimetry (CP) Synthetic Aperture Radar (SAR) architectures to perform sea oil pollution monitoring is analyzed. The Hybrid-Polarity (HP) CP mode, characterized by a right-handed circular transmission and a coherent horizontal/vertical orthogonal receiving basis, is considered. Several HP features are extracted from actual L- and C-band Fully-Polarimetric (FP) SAR data emulating the HP configuration. The behaviour of HP features is physically interpreted using a polarimetric model that allows describing the properties of the partially polarized wave scattered off the sea surface with and without oil slicks. Performance of HP SAR architectures to detect oil spills, characterize their physical/chemical properties and discriminate them from a broad class of look-alikes (i.e., biogenic surfactants) is evaluated and contrasted with the one achieved by FP SARs. Experimental results witness the capability of HP SAR architecture to be operationally used fo sea oil spill observation purposes, achieving performance that tends to the FP one.