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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, a method for retrieving wind speed from synthetic aperture radar (SAR) imagery collected under extreme weather conditions is proposed. The rationale for this approach relies on the fact that, although copolarized channels exhibit saturation for wind speed >~20 m s−1, the wave growth can be successfully exploited to gather information on wind speed under extreme weather conditions. Hence, in this study, the intrinsic relationship among the wind-wave triplets [wind speed at 10 m above the sea surface, significant wave height (SWH), and peak wave period] is exploited in order to retrieve wind speeds under tropical cyclone conditions. Experiments, undertaken on actual X-bandTerraSAR-X(TS-X) SAR images of tropical cyclones (Typhoon Megi, Hurricane Sandy, and Hurricane Miriam) and using collocated WAVEWATCH-III (WW3) simulations, revealed the robustness of the proposed approach, which resulted in a root-mean-square error (RMSE) of 2.54 m s−1when comparing the retrieved wind speeds with the values from products delivered by the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD). However, the applicability of the algorithm herein will be further confirmed at very strong storms.

In this study, a novel physical approach is proposed to detect damages due to earthquakes using dual polarimetric (DP) coherent Synthetic Aperture Radar (SAR) imagery. An optimization method, aimed at enhancing scattering basis differences between measurements collected before and after the event, is designed exploiting Lagrange optimization of the difference between two polarimetric covariance matrices. A meaningful showcase is presented to demonstrate the soundness of the proposed approach that consists of processing Sentinel–1 C–band scenes related to 2016 Central Italy Earthquake. The proposed approach, which is contrasted with the conventional coherence based single– and dual–polarization approaches, results in the best sensitivity to damages.

In this paper, we highlight the importance of high-resolution wind data on the application of multicriteria evaluation technique to colocate offshore wind farms and open-water mussel cultivations. An index of colocation sustainability (SI), based on an environmental information, is constructed using remote sensing data and taking into account both physical constraints (i.e., water depth and wind speed) and environmental data (i.e., chlorophyll-a, sea surface temperature anomaly, and particulate organic carbon). To verify the proposed methodology, five showcases are presented, where SI is evaluated considering potential installation sites in Kattegat, Denmark, using both low-resolution (LR) wind reanalysis maps related to the Modern Era Retrospective-Analysis for Research and Application data set and fine-resolution wind maps obtained by processing synthetic aperture radar (SAR) data. Experimental results show that the availability of a reliable fine-resolution wind information is of great importance in coastal areas where the presence of the land and the isles limits the use of LR wind data.

In this study, the sensitivity of dual-polarization features extracted from dual-polarimetric coherent synthetic aperture radar (SAR) imagery to urban damage due to the earthquake occurred in Centr...

In this study, full-polarimetric synthetic aperture radar measurements are used for coastline extraction and to provide a rough classification of the inland area close to the extracted coastline ac...

In this study, the sensitivity of multi-polarization synthetic aperture radar (SAR) features to vegetation cover is investigated over a test case of environmental importance: the Coiba National Park, Panama. Single-polarization intensity features and polarimetric features derived from the eigenvalue/eigenvector decomposition are analysed and their classification performance, evaluated against a reference land-cover map using a simple clustering algorithm, is contrasted with conventional optical features.Experiments, undertaken using actual L-band full-polarimetric SAR and Landsat data, show that (a) polarimetric information plays a key role in improving the classification accuracy with some polarimetric features performing better than single-polarization and optical ones, (b) classification performance of radar features is significantly affected by incidence angles, and (c) a joint use of different radar features is expected to increase classification accuracy.

In this study, an analysis of the polarimetric synthetic aperture radar (SAR) capabilities to classify coastal areas is undertaken. The Yellow River delta (China) is selected as the test case since it represents an extraordinary environmental and economical area, which is characterized by a very heterogeneous scattering scenario, as witnessed by official reference data, provided by the Chinese government, that classified 12 different kinds of environment. Experimental results, obtained applying two well-known unsupervised classifiers, namely the H/α-based and the Freeman–Durden model-based algorithms, to a fully polarimetric SAR scene collected by Radarsat-2 in 2008 are compared and critically discussed. Both provide a satisfactory global accuracy (larger than 60% in average) with reference to the inland Yellow River delta area, but there are subareas that result in misclassifications and severe classification ambiguities. This study also suggests including single-polarization intensity informatio...

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.

This study proposes a new metric to process dual-polarimetric coherent and incoherent synthetic aperture radar (SAR) data for coastline extraction purposes. The metric, based on the correlation between co- and cross-polarized channels, allows discriminating land from sea in an unsupervised way. Then, simple image processing is adopted to extract continuous coastline from the binary image. Experiments, undertaken on multipolarization C - (RadarSAT-2 and Sentinel-1) and X -band (Cosmo-SkyMed) SAR data collected in South of Italy together with Global Positioning System ground truth, confirm the soundness of the method which is shown to be both effective (a whole SAR scene is processed in seconds) and accurate (the mean error is less than $5$ and $7$ pixels for RadarSAT-2 and CosmoSkyMed, respectively).

In this paper, the most important compact descriptors of wireless propagation channels, i.e. the power delay profile (PDP), the root mean square delay spread $\tau_{\rm{rms}}$ and the probability density function (pdf) of the field amplitude, are emulated with a novel reverberating chamber (RC) measurements method. In particular, the semi reverberating chamber (SRC) is obtained by simply realizing two anechoic corners within the RC. Experiments conducted by employing the RC of the Universita degli Studi di Napoli Parthenope, formerly Istituto Universitario Navale (IUN), on the PDP, $\tau_{\rm{rms}}$ and pdf of the field amplitude, have been compared with theoretical expectation. Furthermore, measurements of multipath channel in a typical working environment, i.e. the IUN research laboratory, are made. Comparisons among the emulated compact parameters and the ones of real life environments, i.e. IUN electromagnetic laboratory, show the soundness of the new proposed technique.

In this paper a new methodology on the characterization of the electromagnetic field in aerospace is shown and discussed. Measurements are made within the Reverberating Chamber (RC) of Universita degli Studi di Napoli Parthenope (formerly Istituto Universitario Navale, IUN) that is an excellent emulator of real aerospace scenarios.

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 ( $\sigma _{\phi _{c}}$ ) 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), $p_{\phi _{c}}(\phi _{c})$ . Experimental results show that the X-Bragg scattering model, here adopted to predict the sea surface $p_{\phi _{c}}(\phi _{c})$ , gives an understanding of the increasing trend of $\sigma _{\phi _{c}}$ with respect to AOI. It is shown that the noise significantly contributes to broaden $p_{\phi _{c}}(\phi _{c})$ over both slick-free and slick-covered sea surface, while the effects of low-to-moderate wind regimes are negligible. In addition, $\sigma _{\phi _{c}}$ exhibits 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.

The objective of the present study is to achieve a better understanding of the possible rotation of embayed beaches using shoreline position data from two beaches on the central Tyrrhenian Sea (Italy) during a 64-year period. With this aim, this study tests the utility of Differential Global Positioning System (DGPS) and GPS RTK (Real Time Kinematic) dual-frequency navigation system for the in situ surveys, low-altitude aerial imagery collected by Unmanned Aerial Vehicle (UAV), and satellite polarimetric Synthetic Aperture Radar (SAR) measurements. The dataset consists of aerial photographs and orthophotos, DGPS, and remote surveys performed by UAV and SAR platform in 2018 along with wave data coming from the Ponza buoy. The results of the field data analysis explained a part of the beach variations in terms of coastline rotation around a virtual pivotal point. This rotation has been correlated with the wave directional shift in the recent period. The results of the comparison between the different techniques gave the possibility to investigate the limitations of remote survey methods for the identification of shoreline rotation.

In this paper, a novel approach is proposed to exploit a time series of COSMO-SkyMed (CSK) HH-VV SAR images to map rice fields and to estimate the sowing dates. The approach relies on multi-polarization features, i.e., the squared modulus of the HH and VV channels and the polarization ratio, extracted from CSK SAR scenes. The key step consists of extracting a rice training signature related to the multipolarization features. This signature allows estimating the sowing date that, at once, is used to refine the rice map obtained by the conventional interpretation of the CSK time series in terms of the scattering mechanisms of the different growing cycles. Experiments, carried out on a time series of 32 CSK images, collected from the Mekong Delta region, South Vietnam, confirm the soundness of the proposed methodology which is shown to provide results comparable to the ones obtained by a literature approach that exploits a similar dataset.

A large time series of 42 dual-polarimetric co-polarized TerraSAR-X (TSX) StripMap Synthetic Aperture Radar (SAR) measurements are exploited to monitor a well-known oil seep area, i.e., the Taylor Energy site in the Gulf of Mexico. A comprehensive scattering analysis is undertaken to assess the impact of SAR imaging parameters (polarization, angle of incidence - AOI, noise floor) and environmental conditions (wind speed - WS, oil properties) on single-polarization SAR-based sea oil seep observation. The main goal of this study is to evaluate the reliability of the scattering-based information derived from the time series of TSX SAR imagery. A two-scale backscattering model is considered to give a physical framework that supports a better understanding of the effects of the above-mentioned factors. Experimental results showed that the high TSX noise floor significantly limits a reliable interpretation of the slick-free sea surface and oil seep backscattering at AOIs larger than 34 and 26, respectively, since they are contaminated by noise. Hence, it is shown that, at larger AOIs, the joint contribution of noisy SAR measurements and low oil backscattering does not result in a larger oil/sea separability. The latter is not remarkably influenced by polarization and WS, under low-to-moderate conditions. Experiments also demonstrate that, when reliable SAR measurements are available, sea oil seep backscattering is affected by the oil's damping properties more than its concentration in the water column. The time variability of the polluted area is also estimated using the time series of TSX imagery and the obtained results agree with independent analysis undertaken on the same test site.

In this study, the effects of speckle filtering in polarimetric Synthetic Aperture Radar (SAR) imagery is investigated for shoreline extraction purposes. In particular, non-local (NL) means filters paradigm is applied to polarimetric SAR measurements in order to derive exact shoreline positions in complex scenarios as sandy beaches. As a showcase, shoreline extraction is undertaken, according to the polarimetric algorithm proposed in [1], from a C-band Radarsat-2 SAR scene covering the historical site of Monasterace (Calabria region, Italy). A preliminary analysis on how to set-up the parameters of the non-local means filter used to reduce speckle noise is undertaken. In addition, in order to evaluate the performance of the non-local means filters to be exploited for polarimetric SAR-based shoreline extraction purposes, a fair comparison with reference polarimetric speckle filters widely used in literature, i. e., the boxcar and the refined Lee filter, is made in terms of accuracy by means of reference Global Positioning System samples considered as ground truth. The NL means speckle filters was shown to outperform the others in terms of accuracy and stability.

Polarimetric Synthetic Aperture Radar (SAR) has powerful capability in marine oil spill detection since it could distinguish clean sea surface from mineral oil spill and false alarms as biogenic thin films. As an alternative to fully polarimetric (FP) SARs, which provide complete scattering information, compact polarimetric (CP) SARs transmit a polarized signal different from conventional horizontal and vertical ones, while receiving coherently the backscattered signal. Hence, they could obtain partial polarimetric information while maintaining a large swath-width, which makes it an ideal tool for marine oil spills observation. However, the proper selection of compact polarimetric SAR modes still remains a critical issue. By transmitting SAR signal with different polarizations, the scattering mechanism of the sea surface can be reflected by different CP SAR features. Hence, it is necessary to analyze the behavior of sea surface scattering as experienced by different CP SAR modes, i. e., different transmitted polarization. In this paper, a unified framework was applied to derive compact polarimetric SAR features under General Transmit and Linear Receive (GTLR) polarization configurations. Following the rationale of polarization signature, the characteristics of features derived by transmitting signals under different roll and ellipticity angles are analyzed. Experiments were conducted on a UAVSAR (Uninhabited Aerial Vehicle SAR) FP SAR image acquired at L-band during an oil-on-water exercise conducted offshore the Norwegian coast, where plant, crude oil, and oil emulsions with different oil-water mixtures were released at sea.

In this study, synthetic aperture radar ocean speckle is exploited to infer information on sea surface wind field. The K-distribution is adopted to model the single look complex vertically/vertically-polarized intensity speckle signal measured over sea surface under different wind conditions, i. e., wind speed and direction. Experiments undertaken on a large set of Sentinel-1 SAR data collected over the northeastern part of the Atlantic ocean, between southern Iceland and northern Scotland, showed that the shape parameter of the K-distribution is sensitive to both ocean wind field and SAR imaging parameters. In particular, it was shown that the shape parameter decreases when increasing wind speed while its variability becomes significant under crosswind relative azimuth angle and at larger incidence angles.

In this study, the performance of antenna-pattern inversion methods is analysed focusing on applications related to the enhancement of the spatial resolution of passive microwave radiometer measurements. In particular, the projection of the reference field onto the kernel of the system function is analysed assuming different radiometer measurements configurations. The analysis shows that one can a priori obtain informations on the performance achievable using antenna pattern deconvolution techniques by analysing the projection of the reference field on the kernel associated to the system function. This allows understanding the role played by the constraints on the sought solution.

Spatial resolution enhancement of microwave radiometer measurements is addressed using a new method that is based on an $L^{p}$ penalisation approach with a variable $p$ exponent. The key idea is letting $p$ to vary in the range 1.2 - 2 to take benefit of both Hilbert (i.e. $p=2)$ and Banach (i.e. $p=1.2)$ advantages. Results, obtained processing both simulated and actual Special Sensor Microwave Imager (SSM/I) measurements, demonstrate the benefits of the proposed approach in reconstructing abrupt discontinuities and smooth gradients with respect to approaches in Hilbert and Banach spaces.

In this paper, a new simple and effective methodology, based on the K–distribution statistical modeling of speckle over sea surface backscattering, is applied on a large dataset of single– look complex (SLC) VV–polarized C–band Sentinel–1 SAR scenes to evaluate the sensitivity of speckle–related parameters, i. e., the K–distribution shape parameter ν, on sea surface wind field. The proposed approach is validated through the time/space co– location of scatterometer winds and precipitation data that are used as reliable source of wind field information.Experimental results show that the K-distribution is suitable to model sea surface speckle and that the latter is informative, i. e., it can be considered as a proxy of sea surface wind speed.

The Reverberating Chamber (RC) is a standard tool for electromagnetic compatibility (EMC) applications and is becoming always more attractive in the wireless applications fields. In this paper, a new RC setup is proposed, i.e. the RC with two anechoic corners (hereinafter the Semi Reverberating Chamber, SRC). This new setup is shown to be a very powerful tool to emulate real life environment, e.g. the indoor. Experiments accomplished at the Universita degli Studi di Napoli Parthenope, formerly Istituto Universitario Navale (IUN) show the good agreement between the actual indoor environment and the SRC measurements in terms of both power delay profile (PDP) and autocorrelation function (ACF).

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.

Coastal geomorphology requires increasingly accurate topographic information of the beach systems to perform reliable simulation of coastal erosion and flooding phenomena, in order to obtain reliable vulnerability assessment. Among the range of remote sensing methods available to produce measurement of the coastline, this study tests the utility of low-altitude aerial imagery by Unmanned Aerial Vehicle (UAV) on the beaches of Serapo and S. Agostino, located in the Latinum region, in the Thyrrenian Sea, and spaceborne Synthetic Aperture Radar (SAR) measurements which are processed with the purpose of exploiting the dual-polarimetric information to better distinguish land from sea.The dataset consists of two sets of images, both acquired by UAV and SAR platforms, the first in December 2013 and the second in June 2018. A comparison of the coastline extraction obtained with the same technique in two different temporal sequences and between different techniques in the same period has been performed in order to assess benefits and limitations of each methodology.

This study aimed at analyzing the effect of Synthetic Aperture Radar (SAR) imaging parameters and environmental conditions on the standard deviation of the co-polarized phase difference ( σ φ C ) evaluated over sea surface. The latter was shown to be an important polarimetric parameter widely used for sea surface target monitoring purposes. A theoretical model, based on the tilted-Bragg scattering, is proposed to predict the behavior of σ φ C against incidence angle for different roughness conditions. Then, a comprehensive experimental analysis, based on the processing of L-, C- and X-band polarimetric SAR scenes collected over different test areas under low-to-moderate wind conditions and covering a broad range of incidence angle, was carried out to discuss the effects of sensor’s and environmental parameters on sea surface σ φ C . Results show that SAR imaging parameters severely affect σ φ C , while the impact of meteo-marine conditions, under low-to-moderate wind regime, is almost negligible. Those outcomes have significant relevance to support the design of effective and robust algorithms for marine and maritime applications based on σ φ C , including the detection of metallic targets (ships and offshore infrastructures as oil/gas platforms, aquacultures, wind farms, etc.) and polluted areas.

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

In this study, a new high-level remote sensing image product is generated by exploiting Global Navigation Satellite System-Reflectometry (GNSS-R) measurements collected by the TechDemoSat-1 (TDS-1) mission. This product consists of normalized radar cross-section (NRCS) measurements arranged in a gridded format. The product is obtained reconstructing NRCSs from actual TDS-1 delay Doppler maps (DDMs) using a deconvolution method based on the two-dimensional (2-D) truncated singular-value decomposition (TSVD). The proposed method is here tested, for the first time, on actual DDMs that include nonhomogeneous areas related to land/sea transition. Experimental results demonstrate that: 1) the gridded product can be successfully reconstructed from actual DDMs; 2) this product is suitable for imaging remote sensing purposes since it exhibits a uniform spatial resolution of $8 \times 30$ km within an area of around $40 \times 40$ km; 3) land/sea transitions, which can be hardly recognized in the DDM, can be well located in the gridded product.

This paper reviews some significant achievements in the research activity and academic career of Paolo Corona, with particular focus on electromagnetic reverberation theory and measurements. An annotated selection is presented for some of his celebrated publications as well as some lesser well-known unpublished works.Some of his recorded views on issues and directions for future research on reverberation chambers are also included.

The quintessence of electromagnetic fields propagating in complex environments is its stochastic nature. The canonical test facility to emulate such a complex case is the reverberating chamber (RC). In order to design, test, and model the electromagnetic field in an RC, one must consider the vectorial nature of the field. The electromagnetic field within an RC has a random 3-D structure that must be properly taken into account to analyze it. A robust and basis invariant analysis of the randomness of such 3-D field is here undertaken estimating the polarization purity, i.e., the degree of polarization. In this paper, a new approach, based on the decomposition of the 3-D degree of polarization, is exploited to analyze the electromagnetic field within an RC. Experiments, undertaken exploiting the RC of Universita degli Studi di Napoli Parthenope, formerly Istituto Universitario Navale (IUN), provide a first experimental validation of the aforementioned decomposition in the microwave range of frequency. In addition, such decomposition, being able to sort out information related to the stability of the polarization ellipse and of the direction of propagation, is a key tool to analyze the effectiveness of the stirring process within the RC.

The sensitivity of COSMO-SkyMed CSK incoherent dual-polarimetric synthetic aperture radar SAR data to the rice growth cycle is investigated here. State-of-the-art scattering models are used, together with a time series of 24 CSK SAR images collected in Mekong Delta, Vietnam in 2014, to interpret the behaviour of multi-polarization features with respect to the different phenological stages that characterize rice growth. Experimental results show the multi-polarization features sensitivity with respect to rice growth cycle and witness that a joint use of the co-polarized channels i.e. co-polarized ratio or correlation between co-polarized channels allows identifying scattering behaviours that are compatible with four stages of the rice growth cycle.

Since 2016 the fracture of the Larsen-C ice shelf has been regularly observed in the Eastern Weddell Sea (68°S, 61°W, Antarctica). This process led to the final collapse in July 2017, when an area of about 6000 km2 (i. e., about 9-12% of the whole shelf) was lost. In this study the resulting calved iceberg, termed as “A-68” from the U. S. National Ice Center, is observed using multi-frequency and multi-polarization Synthetic Aperture Radar (SAR) satellite platforms that include L-band Alos PaISAR-2, C-band Sentinel-l and X-band COSMO-SkyMed. A large set of SAR scenes were considered, collected in ScanSAR imaging modes over a time span of about 1 year, to analyze the iceberg properties and its melting process and drifting.

In this paper, the standard measurement uncertainty (MU) of the insertion loss (IL) in loaded and unloaded continuous mode stirred reverberation chambers (RCs) in presence of both mechanical and frequency stirring is evaluated. The frequency stirring (FS) is essential to increases the total number of uncorrelated samples in an RC; however, when it is combined to a mechanical continuous stirring, a data preprocessing is necessary to check the total number of non-correlated samples. The methodology proposed in this paper is fast and general, i.e., it can be used for several applications of RCs. Since the loading increases the non-uniformity of fields in RCs and it affects the standard MU of the IL, results are also evaluated under the effect of a load.

Oil spills are adverse events that may be very harmful to ecosystems and the food chain. In particular, large sea oil spills are very dramatic occurrences that may affect sea and coastal areas. Hence, the sustainability of oil rig infrastructures and oil transportation via oil tankers is linked to law enforcement based on proper monitoring techniques, which are also fundamental to mitigate the impact of such pollution. In this study, a showcase referring to the Deepwater Horizon (DWH) oil incident, one of the world’s largest incidental oil pollution event that occurred in the Gulf of Mexico in 2010 affecting a sea area larger than 10,000 km 2 , is analyzed using remotely-sensed information collected by Synthetic Aperture Radar (SAR). Although, operationally, SAR sea oil slick observation is typically accomplished using C-band VV-polarized SAR imagery, during the DWH oil incident, because of their very dense revisit time, even single-polarization X-band COSMO-SkyMed (CSK) SAR measurements were collected. In this study, we exploit, for the first time, incoherent dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.

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.

We analyze the uncertainty of measurements carried out in a reverberation chamber. The adopted model includes the frequency stirring method and different $K$ -Factor values. Two majorants are proposed to enhance the uncertainty computation of the chamber insertion loss.

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 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 the context of sea oil slick observation, satellite Synthetic Aperture Radar (SAR) is the most effective remote sensing tool to observe illegal oil spills, support remediation activities and to monitor offshore critical infrastructures as oil fields. Nowadays, the availability of a virtual constellation of polarimetric SARs characterized by multi–polarization, multi-frequency and multi-imaging capabilities offers the unique opportunity to exploit an unprecedented amount of information for sea oil slick observation purposes. In this study, among the different polarimetric features that allow: i) detecting sea oil slicks, ii) discriminating strong– from weak–damping surfactants and iii) providing a spatial zoning of the damping properties of a given surfactant, the standard deviation of the co–polarized phase difference (CPD) is considered. Experimental results, undertaken over a wide dataset of actual SAR imagery collected at different imaging modes (frequency, incidence angle, noise floor, polarization) under different environmental conditions (sea state, type of oil), showed that the standard deviation of the CPD is a reliable and robust polarimetric parameter to perform effective sea oil slick monitoring.

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, typhoon monitoring is addressed using X-band synthetic aperture radar (SAR) imagery collected by the German TerraSAR-X mission and the Italian COSMO-SkyMed constellation during the typhoon Megi. Geometrical features, rain rate, and wind speed associated with the typhoon are retrieved by the SAR data set. One of the key benefits of the X-band observations relies in their sensitivity to rain that can be exploited to provide an estimate of geometrical features and rain rate by analyzing attenuation bands present in the SAR data. In addition, wind speed is retrieved using a rain-free model based on two geophysical model functions (GMFs) and experimental results show that the nonlinear relationship between normalized radar cross section and wind speed provided by one of the GMFs can be exploited to provide a rough estimate of high wind speeds.

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 paper, performance of different indicators for the profiling of Ultra Wide Band (UWB) wireless propagation channel are analyzed. In particular, the γ-indicator and the kurtosis index k are compared in terms of the standard error. In order to improve the accuracy in the kurtosis case, results of the bootstrap error procedure are also accomplished. Further, an evaluation on the computational time needed for error estimation, is also provided. The comparison is made according to a real set of data derived from UWB measurement campaign accomplished within a modern laboratory/office building in which the two above mentioned indicators have been evaluated.

2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018), Observing, Understanding And ForecastingThe Dynamics Of Our Planet, 22-27 July 2018, Valencia, Spain, 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]

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 Universita 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.