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 optimisation method, aimed at enhancing scattering basis differences between measurements collected before and after the event, is designed exploiting Lagrange optimisation 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-polarisation approaches, results in the best sensitivity to damages.

In this article, a two-year time-series of multipolarization Sentinel-1 synthetic aperture radar (SAR) imagery is exploited to analyze the changes in the water-covered area of the Monte Cotugno (Italy) reservoir. A two-step processing chain, which includes water/land separation and waterline extraction, is proposed to accomplish this task. Experimental results, verified using independent in situ measurements, demonstrate that: first, Sentinel-1 time series can be successfully used to support the smart water management of reservoirs. In fact, the changes in the water-covered area inferred from the SAR time series agree with the seasonal behavior and they also fit anomalies; and second, multipolarization feature outperforms single-polarization ones in terms of accuracy of the extracted waterline profile.

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This study deals with coastline extraction using multi-polarization spaceborne Synthetic Aperture Radar (SAR) imagery acquired over coastal intertidal areas. The latter are very challenging environments where mud flats lead to a large variability of normalized radar cross section (NRCS), which may trigger a significant number of false edges during the extraction process. The performance of SAR-based coastline extraction methods that rely on a joint combination of multi-polarization information (either single-or dual-polarization metrics) and speckle filtering (either local and non-local approaches) are analyzed using Global Pointing System (GPS) samples and collocated SAR imagery collected under different incidence angles. Our test site is an intertidal zone with a wetland (i. e., salt marsh) in the Solway Firth, southwest along the Scottish-English border. Experimental results, obtained processing a pair of RadarSAT-2 full-polarimetric and a pair of Sentinel-1 dual-polarimetric SAR imagery augmented by co-located GPS samples, show that: a) the multi-polarization information outperforms the singlepolarization counterpart in terms of extraction accuracy; b) among the single-polarization channels, the cross-polarized one performs best; c) both single-and dual-polarization methods perform better when non-local speckle filtering is applied; d) the joint combination of non-local speckle filter and dual-polarization information provides the best accuracy; e) the incidence angle plays a role in the extraction accuracy with larger incidence angles resulting in the best performance when dual-polarization metric is used.

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