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.

The inversion of the one-dimensional wave spectrum from dual-polarized synthetic aperture radar (SAR) data is performed using machine learning methods, namely Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR) and Convolutional Neural Networks (CNNs). This process incorporates an improved hydrodynamic modulation transfer function (MTF), calibrated with more than 8000 Sentinel-1 (S-1) Ground Range Detected (GRD) images from 2021–2024, to account for shear currents induced by oceanic eddies. This study primarily aims to the differences between algorithm for one-dimension wave spectrum retrieval from S-1 SAR image as passing oceanic eddy and examine the characteristics of sea surface waves change observed by SAR passing through oceanic eddies. SAR retrievals are compared with significant wave heights (SWHs) from Haiyang-2 (HY-2) altimeter and wave spectrum from the Surface Wave Investigation and Monitoring (SWIM) and National Data Buoy Center (NDBC) buoys. The XGBoost model is established as superior for retrieving one-dimensional wave spectra and SWH, recording the lowest RMSE (0.33 m vs. SWIM, 0.30 m vs. HY-2, 0.68 m vs. Buoy) and highest correlation in validation. Applied to a North Atlantic case study, it effectively derives sea states from S-1 image. This high-resolution analysis reveals that oceanic eddies significantly amplify wave energy, resulting in elevated SWH inside their cores. While model accuracy declines in high kinetic energy eddies, the SAR-derived retrievals maintain reliability across eddy-affected regions.

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.

Water ecosystems as oceans, lakes and rivers contribute significantly to global biodiversity, influence the ecological balance and play a remarkable role in different aspects of human society and economy. Therefore, the detection of changes associated to natural and human-induced water dynamics is of great importance for ecosystem preservation, disaster warnings and water conservation projects. To this aims, it is well established that satellite remote sensing tools represent an invaluable source of information.Under this framework, this study focuses on the analysis of dual-polarimetric C-band synthetic aperture radar imaging modes, including compact and linear ones, to extract lake waterline and, therefore, monitor the water-covered area. A reference waterline extraction scheme is adopted for this purpose, which is feed by polarimetric features associated to the two backscattering channels, namely δ and ρ for the compact polarimetric Radarsat Constellation Mission and the linear polarization Sentinel-1 mission. The Athabasca lake in Alberta, Canada, is selected as a meaningful test site. The experimental results show that the dual-polarimetric C-band synthetic aperture radar data can be effectively used to get lake extent information, with subtle differences that apply between RCM compact-polarimetric and Sentinel-1 linear polarization imaging modes.

This study is to discuss the speckle statistics in terms of sea surface roughness and, specifically, in terms of near sea surface wind speed. A data set of Sentinel-1 Synthetic Aperture Radar scenes, acquired under different wind regimes, is processed using normalized intensity moments.

In this study, co- and cross-polarised backscattering signatures over the Terra Nova Bay (Antarctica) coastal polynya imaged by the C-band synthetic aperture radar are discussed. The Terra Nova Bay polynya is of the most important seasonal melting/freezing processes that characterize polar regions by severely impacting ocean circulation and sea ice mass balance. A set of dual-polarimetric synthetic aperture radar measurements collected at C-band over the Terra Nova Bay polynya under different opening and closing conditions are analyzed with the support of ice surface temperature information obtained from optical satellite images. Numerical simulations of backscattering coefficients are also provided according to the improved integral equation method surface scattering model to interpret polynya signatures with and without ice streaks.Experimental results show the potential of dual-polarimetric backscatter coefficients to identify the polynya and its actual conditions and to provide information on its temporal trend even when a single synthetic aperture radar image is available.

In this study, a model-based neural network approach is proposed to retrieve ancillary parameters related to oil pollutants at sea. The proposed methodology consists of two pillars. First, an electromagnetic scattering model is used to generate radar backscatter for slick-free and slick-covered sea surface at variance of incidence angle, faction of water into the oil and oil thickness. Then, these radar backscatter values are combined to generated a metric adopted fro the retrieval process, namely the damping ratio. Second, an artificial neural network is first trained on the simulated damping ratio DR and then applied to actual synthetic aperture radar imagery to retrieve oil thickness and seawater volume fraction. Results, obtained processing synthetic aperture radar scenes collected during the Deep Water Horizon oil accident by the L-band uninhabited aerial vehicle synthetic aperture radar (National Aeronautics and Space Administration - Jet Propulsion Laboratory), show the soundness of the proposed methodology.

This study is to discuss the ability of dual-polarimetric Sentinel-1 Synthetic Aperture Radar (SAR) measurements to observe surface liquefaction occurring during earthquakes.A polarimetric bi-temporal approach is proposed that, combining pre- and co-event SAR imagery, is able to emphasize areas affected by surface liquefaction.The approach is verified using Sentinel-1 SAR scenes related to the Turkey-Syria earthquake occurred in February 2023. The approach is shown to be effective in marking areas where surface liquefaction occurred.

This study is to discuss the ability of full-resolution, i.e., speckled, Sentinel-1 single-look-complex (SLC) Synthetic Aperture Radar (SAR) imagery to monitor water-area coverage of salt ponds. Three scenarios are considered: 1) completely filled of water, 2) empty, 3) intermediate. The metric adopted to track the pond water area evolution is based on the speckle statistics and, in particular, on the departure from the fully developed speckle model.Experiments, performed using a time-series of Sentinel-1 SAR imagery collected over the salt pond "Sale ’e Porcus", Sardinia, Italy, show that Normalized Intensity Moments (NIMs) allow a good separation between the three cases under different wind conditions.

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, a dual-polarization (DP) processing chain is presented to identify lava flow after a volcanic eruption. The proposed methodology is applied to two very challenging case studies, related to the volcanic eruptions that occurred on 24 December 2018 on Mount Etna, Italy, and on 22 May 2021 on Mount Nyiragongo, Democratic Republic of the Congo. The different geomorphology of the two areas together with the different types of lava (i.e., different rheology and rock composition) and surrounding environment is an unprecedented opportunity to analyze the radar polarimetric contribution. First, a DP change detection scheme, which uses a pair of SAR images collected before and after the eruption, is used. Then, the lava flow is detected using a constant false alarm rate detector. Finally, to quantify the performance of the detector, the SAR-based lava flow maps are contrasted with the lava flow footprint provided by Copernicus Emergency Management Service (EMS). Experimental results show that the use of polarimetric information improves lava flow detection in different kinds of environments.

In this study, dual-polarimetric (DP) Synthetic Aperture Radar (SAR) time series collected by the Sentinel-1 SAR mission is exploited to evaluate the changes that occurred over the surface water area of the Po River, in Italy. First, a DP technique based on an incoherent combination of co–and cross-polarized SAR channels are used to enhance the separability between surface river water and land areas. Then, a binary image where the river and the land area are well separated is generated using a constant false alarm rate (CFAR) detector. Once the water-covered area is estimated, an in-depth analysis based on the Shannon entropy is applied to understand the time variability of the water extension of the Po River. Experimental results show that the dual-polarimetric approach can effectively monitor the water body changes that occurred over the river Po basin in an effective way.

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.

The ability to enhance the spatial resolution of measurements collected by a conical-scanning microwave radiometer (MWR) is discussed in terms of noise amplification and improvement of the spatial resolution. Simulated (and actual) brightness temperature profiles are analyzed at variance of different intrinsic spatial resolutions and adjacent beams overlapping modeling a simplified 1-D measurement configuration (MC). The actual measurements refer to Special Sensor Microwave Imager (SSM/I) data collected using the 19.35 and the 37.00 GHz channels that match the simulated configurations. The reconstruction of the brightness profile at enhanced spatial resolution is performed using an iterative gradient method which allows a fine tuning of the level of regularization. Objective metrics are introduced to quantify the enhancement of the spatial resolution and noise amplification. Numerical experiments, performed using the simplified 1-D MC, show that the regularized deconvolution results in negligible advantages when dealing with low-overlapping/fine-spatial-resolution configurations. Regularization is a mandatory step when addressing the high-overlapping/low-spatial-resolution case and the spatial resolution can be enhanced up to 2.34 with a noise amplification equal to 1.56. A more stringent requirement on the noise amplification (up to 0.6) results in an improvement of the spatial resolution up to 1.64.

An enhanced spatial resolution brightness temperature product is proposed for future conical scan microwave radiometers. The technique is developed for Copernicus Imaging Microwave Radiometer (CIMR) measurements that are simulated using the CIMR antenna pattern at the L-band and the measurement geometry proposed in the Phase A study led by Airbus. An inverse antenna pattern reconstruction method is proposed. Reconstructions are obtained using two CIMR configurations, namely, using measurements collected at L-band by the forward (FWD) scans only, and combining forward and backward (FWD+BWD) scans. Two spatial grids are adopted, namely,$3 \mathrm {\,\,km} \times 3 \mathrm {\,\,km}$and$36 \mathrm {\,\,km} \times 36 \mathrm {\,\,km}$. Simulation results, referred to synthetic and realistic reference brightness fields, demonstrate the soundness of the proposed scheme that provides brightness temperature fields reconstructed at a spatial resolution up to ~1.9 times finer than the measured field when using the FWD+BWD combination.

In this study, a new antenna pattern deconvolution method to enhance the spatial resolution of multi -channel microwave radiometer (MWR) measurements is developed. This technique, based on a conventional gradient-like iterative method, utilizes the information contained in a high-frequency channel to enhance the spatial resolution of the lower-frequency channel in a data-fusion fashion. The physical idea consists of initializing the gradient -like inversion scheme using higher frequency details that are filtered out by the system measurement function. Experiments, performed on a dataset that includes both simulated and actual radiometer measurements, show that the proposed technique allows outperforming the conventional gradient method, while being very robust with respect to artifacts that could be induced by the higher frequency channel.

In this study, dual-polarization (DP) C-band Sentinel-1 SAR imagery are processed to generate a damage map related to an earthquake damaged area. A DP change detection scheme, which uses a pair of SAR imagery collected before and after the earthquake, is used. Finally, to quantify the levels of damage a decision tree procedure is exploited. The damaged area refers to the city of Amatrice and its surroundings that were devastated by the earthquake that hit central Italy on 24 August 2016. To generate the damage map and to verify it, ground information provided by Istituto Nazionale di Ge-ofisica e Vulcanologia (INGV) is processed to generate a new index, termed as Weighted Damage Index (WDI). Numerical results show that an accuracy of about 60% can be obtained that confirms the soundness of the proposed approach.

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 letter, a new approach is proposed to ameliorate the performance of iterative gradient-like regularization schemes aimed at enhancing the spatial resolution of microwave radiometer measurements in the Hilbert space. The approach consists of preconditioning the ill-conditioned discrete problem to let the iterative gradient-based inversion technique be more computer-time effective. Experiments undertaken on the simulated radiometer brightness profiles demonstrate the soundness of the proposed rationale that outperforms conventional gradient-like methods in terms of both computer-time effectiveness and accuracy in reconstructing spot-like discontinuities while resulting in larger fluctuations over the background.

In this study, a method to improve the reconstruction performance of antenna-pattern deconvolution based on the gradient iterative regularization scheme is proposed. The method exploits microwave measurements acquired by a multichannel radiometer to enhance their native spatial resolution. The proposed rationale consists of using the information carried on a high-frequency (finer spatial resolution) channel to ameliorate the spatial resolution of the lowest resolution radiometer channel. Experiments performed using both synthetic and real special sensor microwave/imager (SSM/I) radiometer data demonstrate that an enhanced spatial resolution 19.35-GHz channel can be obtained by ingesting in the algorithm information coming from 37.0-GHz channel. This multichannel spatial resolution method is also shown to outperform the conventional gradient-like regularization scheme in terms of both observation of smaller targets and reduction of ringings and fluctuations.

In this study, an enhanced spatial resolution product is proposed for the forthcoming L-band microwave radiometer operated on board of the FSSCat mission. The product is obtained reconstructing the brightness temperature on a finer spatial resolution grid using an antenna pattern deconvolution method. Simulated FSSCat noisy measurements are used to showcase the soundness of the proposed approach that results in remarkable reconstruction performance.

This study addresses the spatial resolution enhancement of synthetic microwave radiometer observations as obtained by the forthcoming Copernicus Imaging Microwave Radiometer (CIMR). An antenna pattern deconvolution scheme is used to exploit the actual L-band CIMR antenna pattern together with a regularization scheme to reconstruct the brightness field at enhanced spatial resolution. Simulation results, referred to synthetic and realistic reference brightness fields, demonstrate the soundness of the proposed scheme that provides brightness fields reconstructed at a spatial resolution up to 1.5 times finer than the measured field.

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.

The detection of wind turbines in a strong clutter background is analyzed at variance of polarimetric synthetic-aperture radar (SAR) configurations. The area of interest is the intertidal zone near Jiangsu, China and two detectors are used, the polarimetric notch filter (PNF) and a change detector that optimizes the ratio between covariance matrices. The detection performance is quantitatively analyzed using the receiver operating characteristic (ROC) curve, while the scattering mechanisms that characterize wind turbines are analyzed using the Yamaguchi decomposition. Experimental analysis shows that: 1) wind turbines result in a nontrivial scattering mechanism and 2) full-polarimetric measurements achieve the best detection performance independently of the two detectors.

In this paper, we introduce a novel approach to enhance the spatial resolution of single-pass microwave data collected by mesoscale sensors. The proposed rationale is based on an Lp-minimization approach with a variable p exponent. The algorithm automatically adapts the p exponent to the region of the image to be reconstructed. This approach allows taking benefit of the advantages of both the regularization in Hilbert (p = 2) and Banach (1 <; p <; 2) spaces. Experiments are undertaken considering the microwave radiometer and refer to both actual and simulated data collected by the special sensor microwave imager (SSM/I). Results demonstrate the benefits of the proposed method in reconstructing abrupt discontinuities and smooth gradients with respect to conventional approaches in Hilbert or Banach spaces.

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.

In this paper, the synthetic aperture radar (SAR) azimuth cutoff method is thoroughly revised and a new and general implementation is proposed. The key roles of the pixel spacing, the size of the image box, and the texture of the SAR scene are analyzed and optimized in terms of azimuth cutoff (λc) estimation. The reliability of the λcestimation is analyzed by measuring the distance between the measured and fitted autocorrelation functions. This analysis shows that it is of paramount importance to filter unfeasible/unreliable λcvalues. To identify those values in an objective way, a criterion that is based on the χ2 test performed over a large data set of Sentinel1 SAR imagery is defined and proven to be effective. The new robust implementation of the λcestimation at about 1-km grid spacing is then used to produce averaged λcat about 10-km grid spacing. The performance of the new estimation procedure, analyzed using a λc-to-wind-speed forward model, is shown to provide improved wind speed retrievals, with a root-mean-square error of 1.8-2 m/s when verified against independent numerical weather prediction model output and scatterometer winds.

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.

We present a novel approach to enhance the spatial resolution of microwave data collected by meso-scale sensors. The proposed rationale is based on an LP-penalization approach with a variable exponent p, ranging in the interval [1.5,2]. This allows taking benefits of the advantages of both Hilbert and Banach spaces. Preliminary experiments undertaken using simulated and actual radiometer data confirm the effective improvement in the signal reconstruction by using this approach with respect to conventional Hilbert and Banach-space methods.

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 study, the azimuth cut-off approach, which is typically adopted to estimate wind speed from Synthetic Aperture Radar (SAR) imagery collected under nominal wind conditions, is discussed with respect to high wind regime cases. First, the key roles played by the pixel spacing, the size of the boxes used to partition the SAR imagery and the image texture (homogeneity) are discussed in terms of their effects on the azimuth cut-off (λc) estimation. Then, the reliability of the λc estimation is analyzed by measuring the distance between the measured and fitted autocorrelation functions (ACFs). This analysis shows that it is of paramount importance to filter unfeasible/unreliable λc values. To identify those values in an objective way a criterion is proposed that is based on the χ2 test performed over a large dataset of Sentinel-l SAR imagery. The effectiveness of the χ2 test is verified by correlating the accepted estimates against auxiliary significant wave height data.

In this study, multi-polarimetric features extracted from dual-polarimetric (DP) Synthetic Aperture Radar (SAR) data collected by the Sentinel-l SAR mission are exploited to analyze damages due to earthquakes. First, conventional single-polarization features, based on the coherence between pre- and post-event imagery, are analyzed using both the co-polarized and the cross-polarized channels to point out that the information carried on the two channels is different. Then, a coherent dual-polarimetric feature, based on the inter-channel coherence, is proposed. Results show that the latter feature allows to detect the changes after an earthquake using only two SAR acquisitions, i.e.; before and after the earthquake. Finally, a change detection algorithm based on the eigenvalues of the difference of covariance matrices, is proposed. Experimental results show that the DP information allows to improve the results obtained by conventional single polarization change detection techniques.

A new study based on the complex and amplitude cross-pol correlation is made. It exploits Sentinel-1 Single Look Complex (SLC) SAR and reference HSCAT wind data. The behavior of these two polarimetric features vs wind speed is analyzed. Low-to-moderate and high wind speed regimes are considered. The study is focused on three subsets characterized by different incident angle ranges. The study shows that in all cases the two polarimetric features are sensitive to wind speed and better behave with respect to$S$vv.

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.

A controlled environment is designed to analyze polarimetric features and decomposition methods for radar remote sensing purposes. The environment is based on the anechoic chamber of Università degli Studi di Napoli Parthenope (UNP) and it exploits a quasi-monostatic antenna configuration that is obtained using a transmitting antenna and two receiving antennas that coherently receive the co- and cross-polarized signals. This allows emulating polarimetric radar measurements related to slecetd targets in a controlled enviroment and, therefore. testing polarimetric radar features and methods. In this abstract, both an incoherent and a coherent analysis are undertaken with the latter exploiting Stokes parameters and eigenvalue decomposition. Experiments undertaking using a man-made depolarizing target confirm the soundness of the approach.

Typhoon is one of the most powerful and destructive natural disasters. Accurate forecasting of Typhoon track and intensity is very important to disaster prevention and reduction. Satellite observations can effectively compensate for the shortcomings of traditional methods of sea surface measurement and provide all-weather observation over the sea surface, which is of great significance to improve the numerical prediction of strong convective weather over ocean. The spaceborne radar observes the backscattering caused by the sea surface roughness, and then, the sea surface wind can be retrieved. The Synthetic Aperture Radar (SAR) is an important data source for sea surface monitoring. A variety of meteorological hydrological elements can be retrieved by SAR observation, and it has been used in data assimilation in recent years [1]. SAR imagery is also used to monitor strength and structure of typhoons [2]. The accuracy of sea surface winds retrieved from SAR has been found to be comparable to that of scatterometer data [3], and these wind fields can be used with a data assimilation system to provide the initial conditions for the numerical weather prediction (NWP) model [4].

In this letter, Global Navigation Satellite System Reflectometry (GNSS-R) delay Doppler maps (DDMs) acquired by the U.K. TechDemoSat-1 (TDS-1) mission are analyzed to identify sea ice infesting waters in circumpolar areas. First, the sensitivity of actual DDM to sea ice is investigated using reference information provided by a Sentinel-1 synthetic aperture radar imagery and a Special Sensor Microwave/Imager based sea-ice concentration map. Then, a new product is proposed that consists of normalized radar cross section measurements derived from actual DDMs and arranged in gridded format. This product is shown to provide spatial information on the sea ice transition that cannot be obtained exploiting the conventional DDM product. Hence, this new product can be used to improve/complement conventional remote sensing techniques for sea ice observation.

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.

The empirical dependence of the azimuth wavelength cut-off on the significant wave height and on the wind speed have been studied. The azimuth cut-off is estimated on the fitting of a Gaussian function to the azimuth autocorrelation function of the radar cross section. The feasibility of estimating the significant wave height and/or the wind speed has been investigated as well. We use SAR images acquired by the European Sentinel 1 from the beginning of November 2014 to the end of April 2015 co-located with the scatterometer winds acquired by the Chinese sensor HSCAT and the significant wave height from ECMWF forecasts. The correlation between the azimuth cut-off and the significant wave height is rather strong. A linear geophysical model function is fitted in order to estimate it. The dependence on the wind speed is secondary and becomes remarkable only when the sea state is fully developed. A significant wave height retrieval exercise is proposed and the results are compared with the buoy measurements of the National Data Buoy Center (NDBC) network.

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.

Global Navigation Satellite Systems - Reflectometry (GNSSR) is an innovative and promising tool for remote sensing purposes. Several applications have been developed to extract geophysical information of the reflected scene from the measured delay waveforms and Delay-Doppler Maps (DDMs). Recently, techniques have been presented to deconvolve the DDMs to reconstruct the Normalize Radar Cross Section (NRCS) field of the observed area in order to provide added value products for imaging remote sensing. In this paper an effective reconstruction scheme, based on the 2-D Truncated Singular Value Decomposition (TSVD), is proposed and succesfully tested on actual Delay Doppler Maps (DDMs) acquired by TechDemoSat-1 (TDS-1) mission.

The German Aerospace Center has opened the TanDEM-X science phase in order to demonstrate new Synthetic Aperture Radar techniques and applications. In particular, the TanDEM-X pursuit monostatic configuration has been switched on from October 2014 till February 2015. This paper investigates the use of the two TanDEM-X satellites to acquire a pair of independent SAR data in single and multi-polarization mode for maritime surveillance applications. Multi-polarization SAR data have shown to be more effective than single-polarization one, for what concern oil spill and ship detection. Here, for the first time has been possible to directly compare almost simultaneous SAR measurements of marine slicks and targets using both single and multi-polarization data. In-situ ground truth data have been collected during satellites overpasses in order to conduct the analysis.

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 paper, a new computer-time effective iterative method is proposed to enhance the spatial resolution of microwave radiometer data in both Hilbert and Banach spaces. The reconstruction method is based on the conjugate gradient (CG) method. CG is a well-known method in electromagnetics, where it is commonly used to address inverse problems in Hilbert spaces. However, the method has never been applied to inverse problems related to spatial resolution enhancement of microwave remotely sensed measurements. In this paper, CG is adapted to the microwave radiometer case and exploited to reconstruct the brightness field at enhanced spatial resolution. Then, CG is, for the first time, extended to Banach spaces by means of duality maps and then applied to enhance the radiometer spatial resolution. Experiments undertaken on both simulated and actual radiometer data confirm the soundness of the proposed approach in Banach spaces and demonstrate that CG is able to provide a reconstruction accuracy similar to the conventional Landweber method, but with a significantly reduced processing time.

A new methodology to estimate the growth stages of agricultural crops using the time series of polarimetric synthetic aperture radar (PolSAR) images is proposed. The methodology is based on the complex Wishart classifier and both phenological intervals and training areas are identified measuring the distances among polarimetric covariance matrices obtained from the time series of PolSAR data. Consequently, the computation of PolSAR features, which is the main step of state-of-the-art methods, is no longer needed, and the proposed approach can be applied in the same way to any crop type. Experiments undertaken on a dense time series of fully polarimetric C-band RADARSAT-2 images, collected at incidence angles ranging from 23° to 39°, in ascending/descending orbit passes, demonstrate that the proposed methodology can be successfully applied to retrieve the phenological stages of four different crop types. In addition, the effect of combining beams corresponding to different sensor's configurations has been evaluated, showing that it affects the retrieval accuracies. Validation with ground data shows the following: overall accuracy is between 54% and 86%; producer's accuracy (PA) and user's accuracy (UA) range between 21% and 100% and between 33% and 100%, respectively.

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.

In this study application results are presented derived from multi-parametric SAR observations covering five different thematic domains: forest, agriculture, ocean, urban and cryosphere. In total 21 application products have been selected and described. Their application on different data sets, space- and airborne sensors, was demonstrated and can independently be reproduced by any scientist. The results and algorithms are available soon through Springer.

An innovative technique, based on a generalization of the conjugate gradient (CG) method in Banach spaces, is first proposed to enhance the spatial resolution of microwave radiometer measurements. This approach allows reducing the over-smoothing effects and the oscillations that are often present in Hilbert reconstructions and it is very effective in terms of processing time. Experiments undertaken on actual SSM/I data confirm the soundness of the proposed approach and show that CG is able to provide reconstructions similar to the conventional Landweber ones but with a significantly reduced processing time.

In this study the spatial resolution of microwave data collected by the AMSR-E radiometer is enhanced to evaluate wind speed on a spatial grid finer than the conventional one. The spatial resolution problem is addressed in both Hilbert and Banach spaces and experiments are undertaken on actual data collected over the North Sea. Results show that the spatial resolution of the 6.9 GHz channel can be improved to approximately meet the 10.7 GHz one and, hence, this allows estimating wind speed using a finer resolution grid.

C-band RADARSAT-2 quad-Poland X-band COSMO-SkyMed incoherent dual-polarization PingPong SAR data are used to monitor corn fields phenology. The polarimetric analysis carried out at C-band shows a sensitivity of polarimetric observables to corn phenology that allows to interpret the different polarimetric signatures occurring along the cultivation cycle. Unfortunately, at the X-band, a physical interpretation is not properly provided, due to the unavailability of radar acquisitions for the most of the cultivation cycle. This is due to defense requirements which caused conflict acquisitions with the planned COSMO-SkyMed SAR data.

This study aims at addressing coastline extraction and coastal area classification using a new polarimetric SAR (polSAR) architecture, namely the Hybrid-polarity (HP) architecture that belongs to the class of compact-polarimetric (CP) SAR. First the continuous coastline is extracted using HP features; then, the inland area is classified according to the dominant scattering mechanism. Experiments undertaken using HP data emulated starting from actual fine-quad polarimetric RadarSAT-2 SAR data confirm the soundness of the proposed approach.

Global Navigation Satellite Systems - Reflectometry (GNSS-R) represents an innovative tool for imaging remote sensing. It has been recently shown that inverting a determined system it is possible to generate a key remote sensing added value product: the radar image of the reflecting scene. This process is strongly influenced by the Delay-Doppler (DD) resolution that depends on the hardware/software resources. Moreover, another important issue is related to the high cost in terms of data storage when collecting the full DDM. In this paper, a resolution enhancement method to ameliorate GNSS-R imaging applications in terms of software/hardware and storage resources consuming, based on the inversion of an undetermined ill-posed problem, is presented.

Global Navigation Satellite Systems - Reflectometry (GNSS-R) is an innovative and promising tool for remote sensing purposes. Several applications have been developed to extract geophysical information of the reflected scene from the measured delay waveforms and Delay-Doppler Maps (DDMs). Recently, techniques have been presented to deconvolve the DDMs to reconstruct the Normalize Radar Cross Section (NRCS) field of the observed area in order to provide added value products for imaging remote sensing. In this paper an effective reconstruction scheme, based on the Conjugate Gradient approach operating in Banach space, is proposed and successfully tested on simulated marine scenario.

A simple innovation that enables a faster convergence rate of iterative gradient-like descent approaches is proposed and applied to linear image reconstruction problems from irregular sampling. The key idea is to reduce the amount of regularization effects of the conventional Tikhonov functional by introducing a negative seminorm penalty term, whose role is to speed up the convergence without reducing the reconstruction accuracy. The method is employed to enhance the spatial resolution of microwave remotely sensed products. First experiments, undertaken on simulated radiometer data, demonstrate that the technique significantly increases the convergence rate, halving the number of iterations when applied to speed up the basic and widely used Landweber method.

Global Navigation Satellite System-Reflectometry (GNSS-R) is a promising and innovative remote sensing technique. In this letter, an investigation on the polarimetric characteristics of GNSS-R signals is performed. The study is conducted by means of an ad hoc simulator based on a facet approach to approximate a 3-D time-domain generated sea surface. To best mimic a realistic configuration, the simulator uses both recorded GPS and Galileo signals as incident waves. The effect of the incoherent averaging in mitigating the speckle is shown. Finally, a relationship between the wind speed and the polarimetric ratio is analyzed.

Most of the inverse problems arising in applied electromagnetics come from an underdetermined direct problem, this is the case, for instance, of spatial resolution enhancement. This implies that no unique inverse operator exists; therefore, additional constraints must be imposed on the sought solution. When dealing with microwave remote sensing, among the possible choices, the minimum p-norm constraint, with 1preconstructions for 12ones when spot-like discontinuities are considered; when dealing with abrupt discontinuities, l2and lp reconstructions are characterized by similar performance; however, lpreconstructions exhibit oscillations when the background is not properly accounted for.

In this paper a polarimetric SAR data study is undertaken over the critical and peculiar case of the Deepwater Horizon (DWH) oil spill accident occurred in the Gulf of Mexico in 2010. It is a complex case that still calls for deeper physical/chemical characterization due to its special nature. Such an oil spill accident is in fact related to a deep/ultra-deep sea drilling, that although of paramount interest in gas and oil exploitation, need special care and safety actions to manage high oil pressure and potential vast environmental oil spill long-term and short-term impact.

Global Navigation Satellite Systems - Reflectometry (GNSS-R) represents an innovative tool for remote sensing. In this paper a facet-based simulator is presented to investigate the polarimetric characteristics of GNSS L-band signals reflected off sea surface. The aim of the proposed technique is to improve the classical simulation technique based on the Zavorotny-Voronovich (Z-V) approach. Therefore, the scattered power and the Delay-Doppler Map are obtained using a time-evolving random 3D sea surface and the Kirchhoff Approximation (KA) of the Physical Optics (PO) to describe the scattering mechanisms. Finally the polarization ratio (PR) between co- and cross-polar scattered signal is fully investigated against different sea surface conditions, i.e. wind speed.

A two-step physically consistent procedure is proposed to exploit COSMO-SkyMed (CSK) synthetic aperture radar (SAR) data acquired in the incoherent dual-polarization PingPong mode. The first step, which deals with land/sea discrimination, is accomplished in a robust and effective way by exploiting the inherent peculiarities of the CSK PingPong mode. Hence, a dual-polarization scattering model that relates the correlation between the HH and VV CSK polarimetric channels to the coherence time of the observed scene is first proposed. The second step, which deals with the extraction of the continuous coastline, is accomplished by a simple image processing that consists of extracting intermediate frequency components using two Gaussian-shaped filters. Experiments undertaken over actual CSK single-look slant range complex PingPong HH/VV SAR data show the physical soundness of the proposed rationale and the processing effectiveness.

A reconstruction technique, mathematically based on a generalization of the gradient method in Banach spaces, is first proposed to enhance the spatial resolution of radiometer earth observation measurements. This approach allows reducing the over-smoothing effects and the oscillations that are often present in standard Hilbert-spaces procedures without any drawback on the numerical complexity. Experiments undertaken on a data set consisting of both simulated and actual 2-D special sensor microwave imager radiometer measurements show the accuracy and the effectiveness of the proposed technique. A typical radiometer scene is processed in few minutes by a standard PC processor. Furthermore, since the proposed approach is iterative, the processing time increases slowly with the problem's size.

A reconstruction technique, based on the 2-D truncated singular value decomposition, is first proposed to enhance the spatial resolution of radiometer earth observation measurements. The technique is very computer time effective when the kernel is a 2-D tensor product. The key issue regarding the selection of the truncation parameter is addressed by the statistically based generalized cross-validation approach. Experiments undertaken on a data set consisting of both simulated and actual 2-D special sensor microwave imager radiometer measurements show the robustness of the technique against the additive noise and its effectiveness in terms of processing time. A typical 2-D radiometer scene is processed in seconds by a standard PC processor.

Ship detection with Synthetic Aperture Radar is a largely investigated topic and a series of operational algorithms are currently exploited by the users community. Polarimetry may play an important rule in this context, since the next generation of SAR satellites will be able to perform large swath polarimetric (either dual or compact) acquisitions. In this work, a comparison of promising ship detectors employing polarimetric information is performed over an ALOS-PALSAR quad-polarimetric dataset acquired over Tokyo Bay (October 2008). Interestingly, a survey of the area is available allowing to provide some quantitative comparison of the different detectors. The results show that the quad polarimetric detectors return better detection performance than the dualor single-polarimetric ones.

In this study recent advances in Synthetic Aperture Radar (SAR) polarimetry to observe sea oil slicks and man-made metallic targets are reviewed in the frame of the ESA funded PolSAR-Ap project. The most up-to-dated quad-pol approaches to observe sea oil slicks and metallic targets are reviewed and their performance is discussed against conventional single- and dual-pol approaches using actual L- and C-band Single Look Complex (SLC) SAR data. The unique benefits of quad-pol SAR data to observe both oil slicks and metallic targets are clearly shown.

A dual-polarimetric approach to extract coastline using dual-polarimetric coherent HH, HV SAR data is first proposed. The approach is physically based and exploits: a) the different symmetry properties that characterize land and sea, to allow a robust land/sea separation; b) simple image processing, to extract the coastline. The approach is verified against actual RadarSAT-2 SAR data and it is shown to be both effective (a typical SAR scene is processed in seconds) and accurate.

ScanSAR is a synthetic aperture radar (SAR) acquisition mode particularly suitable to several environmental applications due to its very large swath. This mode, once operated by virtual or real constellations, is able to remarkably reduce the revisit time, and this is of great relevance in all marine applications. Unfortunately, this particular kind of acquisition is affected by an intrinsic phenomenon, called scalloping, that hampers image interpretation, particularly in the case of data acquired over the sea. In this letter, an innovative and computationally efficient postprocessing procedure is presented in order to get rid of scalloping in ScanSAR data. Experiments accomplished over multilook ground-detected SAR COSMO-SkyMed data confirm the physical soundness of the proposed technique.

A physical dual-polarimetric model to observe man-made metallic targets at sea in dual-polarimetric coherent X-band synthetic aperture radar (SAR) data is proposed. The model exploits the intrinsic different symmetry properties of man-made targets and sea surface and is tested over actual StripMap TerraSAR-X HH-HV and VV-VH dual-polarimetric SAR data and colocated ground truth measurements. Then, an operational physically based filter to observe targets at sea is proposed. The filter is very attractive in terms of both detection performances and processing time. A typical SAR scene is processed in seconds by a conventional PC processor.

A reconstruction technique based on the two-dimensional truncated singular value decomposition (TSVD) is first presented to enhance the spatial resolution of radiometer earth observation (EO) measurements. The technique is physically based on the assumption that the antenna gain function is separable. This hypothesis allows implementing a very computer time effective TSVD-based resolution enhancement technique. Experiments undertaken on a data set of both simulated and real two-dimensional radiometer measurements show a) the accurancy of the proposed approach, b) its robustness against the additive noise level, c) its effectiveness in terms of processing time.

In this paper, a preliminary validation study of the Azimuth cut-off procedure is presented for the X-band COSMO-SkyMed© SAR-based wind speed estimation. The data set consists of 100 sub-images excerpted by X-band Level 1B Stripmap HImage COSMO-SkyMed© SAR data, gathered in the geographic area of Mediterranean Sea on 2009. The validation is accomplished by using the ground truth provided by timely and spatially co-located QuikSCAT scatterometer data. Experimental results demonstrate the effectiveness of the proposed approach taking full benefits of X-band COSMO-SkyMed© SAR data.

In the paper are presented some of the main outcomes of the projects, relevant to marine monitoring, developed in the framework of the first Announcement of Opportunity Cosmo-SkyMed. The principal subjects covered are: ship detection, oil spill monitoring, wind retrieval, sea surface currents estimation and coastline extraction.

COSMO-SkyMed (CSK) dual-polarized Synthetic Aperture Radar (SAR) data, acquired in PingPong mode, are first exploited to extract coastline. A dual-polarization model that takes full benefit of the PingPong mode peculiarities is developed to distinguish sea surface from land. Following this rationale, a physically-based filtering technique is proposed to extract the coastline in full-resolution CSK SAR data. Experiments confirm the soundness of the proposed approach and its effectiveness in terms of processing time.

The Scanning Synthetic Aperture Radar (ScanSAR) is a powerful and widely used acquisition mode for Earth observation because of its huge imaging swath and short revisit time. These peculiarities make ScanSAR mode more advantageous of others SAR acquisition modes, in order to provide data suitable for marine applications. Data are obtained by recording backscattered signals from multiple sub-swaths in an altering manner, i.e. ScanSAR disperses the transmitted pulses to several beams by activating each beam intermittently.

A dual-polarimetric model to exploit PingPong mode X-band full-resolution COSMO-SkyMed (CSK©) SAR data for metallic targets observation purposes is developed. The model relates the correlation between the co-polarized channels, in case of sea surface with and without metallic targets, to the time leg between two successive bursts. Experiments undertaken over COSMO-SkyMed Single Look Complex Slant (SCS) PingPong SAR data demonstrate the soundness of the proposed approach and its effectiveness from an operational viewpoint.

In this study the capabilities of full-resolution Single Look Complex Slant (SCS) ScanSAR Wide Region mode X band COSMO-Sky Med© Synthetic Aperture Radar (SAR) data are exploited to detect metallic objects over the sea. A physically-based filtering technique is developed which, based on the coherent-to-incoherent field ratio (Rice factor), is able to detect even small metallic objects in X-band full-resolution SAR data. Experimental results show the effectiveness of full resolution SCS ScanSAR Wide Region mode X-band COSMO-SkyMed© SAR data to observe small metallic objects at sea.

Within the National Environmental Satellite, Data, and Information Service, National Oceanic and Atmospheric Administration, multiplatform synthetic aperture radar (SAR) imagery is being used to aid post hurricane and postaccident response efforts in the Gulf of Mexico, such as in the case of the recent Deepwater Horizon oil spill. The main areas of interest related to such disasters are the following: (1) to identify oil pipeline leaks and other oil spills at sea and (2) to detect man-made metallic targets over the sea. Within the context of disaster monitoring and response, an innovative processing chain is proposed to observe oil fields (i.e., oil spills and man-made metallic targets) using both Land C-band full-resolution and fully polarimetric SAR data. The processing chain consists of two steps. The first one, based on the standard deviation of the phase difference between the copolarized channels, allows oil monitoring. The second one, based on the different symmetry properties that characterize man made metallic targets and natural distributed ones, allows man made metallic target observation. Experiments, accomplished over single-look complex L-band Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) and C-band RADARSAT-2 fully polarimetric SAR data gathered in the Gulf of Mexico and related to the Deepwater Horizon accident, show the effectiveness of the proposed approach. Furthermore, the proposed approach, being able to process both Land C-band fully polarimetric and full resolution SAR measurements, can take full benefit of both the ALOS PALSAR and RADARSAT-2 missions, and therefore, it allows enhancing the revisit time and coverage which are very critical issues in oil field observation.

A study exploiting dual-polarimetric X-band synthetic aperture radar (SAR) data to observe oil at sea is undertaken for the first time. The polarimetric model exploits the interchannel correlation between the like polarized channels. Accordingly, two parameters related to the interchannel correlation, namely, the amplitude coherence and the copolarized phase difference (CPD) standard deviation, are accounted for, and their performances, with respect to sea oil slick observation, are carefully discussed. Single-look Slant range Complex dual-polarized TerraSAR-X SAR data, in which both certified oil slicks and weak-damping look-alikes are present, are used to verify the efficiency of the proposed approaches. Results show the advantage of the CPD approach and the effectiveness of TerraSAR-X dual-polarized products for such application.

In this study, two innovative physically-based approaches have been developed to detect man-made metallic objects and oil slicks in polarimetric SAR data. They are based on the different sea surface scattering mechanisms expected with and without oil slicks and metallic objects. Experiments, accomplished over Single Look Complex (SLC) Level 1.1 quad-pol L-band ALOS PALSAR SAR data, demonstrate the effectiveness of the two approaches for oil slick and metallic target detection purposes and witness the capability of ALOS PALSAR data for such applications.

An electromagnetic model to observe man-made metallic objects in dual-polarized SAR data has been developed. The model predicts that man-made metallic objects and sea surface, being characterized by completely different symmetry properties, call for a different and well-distinguishable HH-HV correlation. Following this rationale, a simple and very computer-time effective filtering technique has been developed to observe man-made metallic objects in full-resolution dual-polarized SAR data. Experiments accomplished over Single Look Complex (SLC) Fine Quad Polarization RADARSAT-2 SAR data confirm the effectiveness of the proposed approach.

In this study single look complex (SSC) TerraSAR-X dual-polarized data are firstly exploited for sea oil slick observation purposes. An electromagnetic model which, based on the Co-polarised Phase Difference between the HH and VV channels (CPD), allows describing the X-band sea surface scattering with and without surface slicks is proposed. Following this rationale, the polarimetric approach is firstly developed and applied to X-band Synthetic Aperture Radar (SAR) data in which both certified oil slicks and look-alikes are present. Experimental results demonstrate, for the first time, that X-band dual-polarimetric SAR data are suitable for sea oil slicks observation purposes and witness the paramount importance of the TerraSAR-X dual-polarimetric mode for such application.

Bragg scattering is widely recognized as the dominant mechanism at moderate incident angles, by which the ocean surface backscatters microwave radiation. In this paper we have shown that the validity domain of the Bragg/composite surface theory can be extended to low grazing angles by taking into account the contribution of second order scattering effects into the first order at small scale. An improved two scale model (TSM) has been investigated at low grazing angles for (radar frequencies) L-, C- and Ku-band with wind speeds of 7 m/s and 15 m/s. It is observed that for higher wind speeds the intensity of ¿HHincreases up to 8 dB. In backscattering configuration predictions of the model are compared with the experimental data at Ku-band. Comparison shows good agreement at higher wind speeds. Finally, we use the improved TSM to predict the sea scattering in bistatic configuration and compare the results with classical TSM.

In this study an electromagnetic approach is proposed for exploiting polarimetric information for sea oil slick observation in L-band ALOS PALSAR full polarimetric SAR data. The problem is tackled form an electromagnetic viewpoint by describing the sea surface scattering mechanism with and without oil slicks. Following this rationale, a filtering technique, based on the Mueller scattering matrix, is applied to detect oil slicks in full polarimetric SAR data. Successively, the filtering results are verified by the analysis of the slick-free and slick-covered pedestal height and polarimetric entropy (H). Experiments, accomplished on a meaningful set of Level 1.1 L-Band ALOS PALSAR full polarimetric data, demonstrate the effectiveness of the proposed approach.

In this study, a novel unified theoretical framework to describe the polarimetric sea surface scattering with and without surface slicks, entirely based on the Mueller scattering matrix, is proposed. Dealing with slick-free or weak-damping-slick-covered sea surface a Bragg scattering mechanism is expected, while, a non-Bragg scattering mechanism is expected in case of oil-covered sea surface. Following this rationale, the Mueller scattering matrix is physically read in terms of slick-free and slick-covered sea surface scattering mechanisms, through the analysis of some Mueller based polarimetric descriptors, i.e. the degree of polarization, the statistics of the phase difference and the pedestal height. Experiments accomplished on Level 1.1 full polarimetric L-band ALOS PalSAR data confirm the effectiveness of the proposed approach.

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.

Sea oil slick observation by means of synthetic aperture radar is still a scientific and operational challenge. In this paper, the sea surface scattering with and without biogenic slicks is analyzed by using the two-scale Boundary Perturbation Method scattering model. The surface slick is supposed to modify both the full-range sea surface spectrum and the slope probability density function by means of the Marangoni damping and by a reduced friction velocity. In this paper, the full-range Universite Catholique de Louvain sea surface spectrum is considered. A new contrast model, which overcomes the drawbacks of the contrast model based on the untilted Small Perturbation Method scattering model, is presented and illustrated in some L- and C-band biogenic slick cases.

A novel approach to oil-spill classification, based on the paradigm of one-class classification, is proposed. Basically, a classifier is trained using only examples of oil-spills, instead of using oil-spills and look-alikes, as in two-class approaches. In addition, as a large number of candidate features have been considered in the literature, a feature selection algorithm, to objectively select the most effective subset, is proposed. Results on two case study datasets are reported to validate the proposed approach.

In this paper a novel approach for oil spill observation, based on partially polarimetric Synthetic Aperture Radar (SAR) data, is proposed. A model which relates the co-polarized phase difference (CPD) to the sea surface scattering mechanism with and without slicks is developed. Experiments accomplished over multi-look complex (MLC) C-Band SAR data, show that the CPD approach is useful both to observe oil spills and to distinguish between oil spills and biogenic slicks.

This paper describes a new two-scale polarimetric contrast model based on the Boundary Perturbation Model (BPM). The damping of the short gravity-capillary surface waves by small slicks is modelled by the Marangoni damping coefficient. The surface slick is supposed to modify both the short wave part of the sea surface spectrum intensity and the wind input. The model has been validated over SIR-C/X-SAR Multi Look Complex (MLC) L- and C-band Synthetic Aperture Radar (SAR) data.

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.

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.

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.

Marine dark features in SAR imagery related to oil spills, biogenic look-alikes and low wind areas are analyzed by means of the wavelet polarimetric signature (WASP) tool. The WASP encapsulates in a graph the dependency of the wavelet variance on dyadic scale and polarization state. Experiments on SIR-C/X-SAR C-band data showed the effectiveness of this analysis in characterizing textural features of the areas of study.

A speckle model to characterize low backscatter areas and areas with strong scatterers in marine SLC SAR images is presented. The model allows using high resolution speckled SAR images instead of dealing with multi-look SAR images where, at the expense of a poorer spatial resolution, the speckle is mitigated. The new approach is based on the use of the three parameters of the generalized K probability density function. This speckle model embodies the Rayleigh, the Rice and the K-distribution scattering scenes, which are descriptors of scenes dominated by Bragg scattering, scenes in which a dominant scatter is present and scenes with a non-Gaussian signal statistic, respectively. A large data-set of ERS 1/2 SLC SAR images, provided by the ESA under the Project C1P-2769, is employed. Results show the effectiveness of the approach.

This paper describes a synthetic aperture radar (SAR) sea surface waves simulator. The simulator, based on the velocity bunching (VB) theory, has been developed and implemented modularly and its use can also assist microwave remote sensing courses. The present version of the software is run in classes at National Oceanographic Centre of Southampton (NOCS), UK and at the Universita di Napoli Parthenope, Italy.

Interferometric synthetic aperture radar processing requires interpolating a slave image onto a master one. Since the signals requiring interpolation are limited in both time and bandwidth, the Knab sampling window provides an almost optimal and viable interpolation kernel. Its performance in terms of coherence preservation and interferometric phase error as a function of the number of retained samples and oversampling factor are shown.

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

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.

We present a study on the electromagnetic scattering of sea surface based on the Integral Equation Method (IEM), in which the sea roughness spectrum is approximated by a power-law analytical expression. This allows extending the usual first-order IEM approach.

In this paper a sensitivity study of the truncated singular value decomposition (TSVD) for spatial resolution enhancement of radiometric data is detailed. A large set of meaningful experiments is presented and discussed.

The Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission of the European Space Agency (ESA) aims to provide a global and precise soil moisture estimation over land and salinity content over oceans. In this paper we focus on ocean application of the SMOS mission. The brightness temperature of the sea surface with small or moderate roughness is computed with the IEM method, using an analytical n-dependent power-law spectrum that describes the sea-state conditions. Then, the accuracy of the brightness temperature computation with the number of terms of the n-power spectrum is determined. Furthermore, its variation with wind speed is also analyzed.

In this paper we present a scatterometer inversion procedure capable to deal with data frames in which we have triplets and doublets. This is actually the case of the Wind SCatterometer (WSC) on board of the ERS-2 satellite over the Mediterranean Sea. A set of meaningful experiments is presented.

Estimation of digital elevation maps from electromagnetic signals received at an interferometric synthetic aperture radar (SAR) requires significant processing. In this framework, a key step is the interferometric registration, which can be mathematically framed as an interpolation procedure. A new interpolation kernel for SAR interferometric registration is presented and discussed in comparison with five classical ones. It is based on the Knab sampling window that has been successfully employed in various electromagnetic problems and which has been proposed as capable of best preserving the stochastic information. The numerical experiments show the superiority of the new interpolation kernel.

A comparative study regarding the interpolation of stochastic electromagnetic band-limited signals in synthetic aperture radar (SAR) interferometry is detailed. It is shown that the most appropriate interpolation scheme to minimize the coherence losses is the one based on the Knab Sampling Window kernel.

A study regarding the use of the truncated singular value decomposition (TSVD) for the solution of inverse microwave radiometry problem is presented and discussed by means of a set of examples.

The relationship between the normalized radar cross section /spl sigma//spl deg/ and the ocean surface wind field, i.e., the geophysical model function, is a key element in scatterometry. Due to many unsolved physical modeling problems, only a semi-empirical approach can be used to quantitatively relate the observed /spl sigma//spl deg/ to the wind field. Once the appropriate functional form has been selected, a model calibration procedure based on colocated /spl sigma//spl deg/ measurements and external wind field observations/determinations is accomplished. To this end, a /spl sigma//spl deg/ data grouping (binning) is performed to limit measurement uncertainties and reduce data volume. On this note, the binning procedure is revisited as an histogram estimation procedure and the relevant errors are determined. It is shown that in the best case of wind field error-free model the bias error introduced by the binning is negligible (but for low wind regimes) while the variance error is significant.

A novel across-track interferometric synthetic aperture radar (SAR) raw signal simulator is presented. It is based on an electromagnetic backscattering model of the scene and an accurate description of the SAR system impulse response function. A set of meaningful examples are also presented. They show that the proposed simulator is structurally consistent and correctly simulates the decorrelation effect, both in the mean and in the distribution sense.

Simulation of synthetic aperture radar (SAR) raw signal pertaining to an ocean scene is presented. It embodies the distributed surface model, the hydrodynamic modulation, and the Bragg dominant scattering mechanism. Simulation experiments are provided.

The authors exploit the interferometric multifrequency potentiality of the SIR-C/X-SAR system which is equipped with an L-, C-, and X-band sensor. They present a solution to improve the unwrapping performance of the C- and X-band data by considering the L-band unwrapped pattern. A new algorithm for the generation of a single digital elevation model (DEM) combining L-, C-, and X-band information is presented. This solution is based on the fusion of the unwrapped phase patterns by using a Kalman filter. The proposed fusion operation also accounts for the coherence characteristics of the three data sets. The selected test site is the Mt. Etna region in Italy which is very interesting from the volcanological and geological point of view. Numerical assessments of the achieved results are provided by evaluating the height accuracy with respect to a reference DEM.

Deals with the simulation of synthetic aperture radar (SAR) raw signal of actual ground sites described in terms of sparse input data. Since in most cases the input data reference system does not match SAR requirements, it is necessary to adopt appropriate interpolation schemes. The authors focus their attention on elevation input data, noting that natural surfaces exhibit fractal properties. Fractal and nonfractal interpolation schemes are discussed and applied. Simulated images are shown and compared to actual examples. Subjective and objective tests validate the simulation and support the fractal-based elevation interpolation.>

An SAR simulator of an extended three-dimensional scene is presented. It is based on a facet model for the scene, asymptotic evaluation of SAR unit response, and a two-dimensional fast Fourier transform code for the data processing. Prescribed statistics of the model account for a realistic speckle of the image. The simulator is implemented in Synthetic Aperture Radar Advance Simulators (SARAS), whose performance is described and illustrated by a number of examples.>