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Single-pass interferometric synthetic aperture radar (InSAR) is an effective technique for sea ice topographic retrieval despite the inherent dynamics of sea ice. However, the penetration of microwaves into snow-covered thick ice and the achievable height sensitivity for tens-of-centimeters thin ice are two major issues, which limit the accuracy of InSAR-derived sea ice topography. Polarimetry provides scattering information concerning the sea ice properties and has the potential, in combination with interferometry, to achieve an accurate reconstruction of a sea ice digital elevation model (DEM). This article studies the relation between polarimetric signatures and sea ice topography, and explores the possibility to compensate the penetration bias by merging copolar coherence into InSAR processing. The newly generated topographic map has a root-mean-square error under 0.3 m. For thin ice below 1 m, a positive relation between copolar phase phi(coPol) and surface height is observed, suggesting that fcoPol can effectively characterize thin sea ice topography. For thick ice with ridges, the maximum polarimetric phase difference Delta phi(maxPol) reveals a particular shape of the coherence region, which can be interpreted as oriented volume scattering. It suggests that the model-based approach using polarimetric SAR interferometry assuming an oriented volume scattering model is promising in measuring the scattering centers in thick and deformed sea ice. The study of polarimetric behavior for the InSAR DEM is, therefore, a step forward toward accurate modeling of sea ice topography from polarimetric single-pass InSAR data., IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, ISSN:1939-1404, ISSN:2151-1535

The marine atmospheric boundary layer (MABL) roll plays an important role in the turbulent exchange of momentum, sensible heat, and moisture throughout the boundary layer of tropical cyclones. Hence, rolls are believed to be closely related to storm development and intensification. In this study, based on the RADARSAT-2 dataset including various tropical cyclone (TC) intensities, the roll characteristics are retrieved from synthetic aperture radar (SAR) images via fast Fourier transform (FFT). We investigate the roll wavelengths at variance of TC intensities and found that the roll wavelengths are related to the distance with respect to TC center and TC intensities. This study is promising to bring roll-induced effects into hurricane forecasting model.

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 the era of big data for synthetic aperture radar (SAR), multiple SAR systems have come into service, including Sentinel-1. The support of large-volume datasets is the key to the deep interpretation of ship targets in Sentinel-1 imagery. In this paper, we present OpenSARShip 2.0, the newest and upgraded version of OpenSARShip, which is dedicated to the deeper interpretation of SAR imagery for marine surveillance. Based on the higher requirements for ship target interpretation, the OpenSARShip 2.0, covering 34528 SAR ship chips with automatic identification system (AIS) information, possesses three improvements: large volume, interference labeling, and type levels, which are described in this paper. In addition, an application case involving the geometric parameter extraction is introduced to demonstrate the applicability of the large dataset.

Performance of ship detection is influenced by synthetic aperture radar (SAR) imaging characteristics and environmental conditions. In this paper, aiming at evaluating vessel detectability for Sentinel-1 SAR data, a model based on a large-scale Sentinel-1A vessel chips database is established. The model sensitivity is analyzed by simulation data. In the experiment, by inputting the parameters of imaging characteristics (incidence angle, polarization, spatial resolution) and environmental conditions (wind speed, wind direction, sea state) of a specific Sentinel-1 image, the minimum detectable vessel length can be estimated. Further validations demonstrate the availability of the estimated minimum detectable vessel length.