Detection of Wind Turbines in Intertidal Areas Using SAR Polarimetry

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

On the Ability of PolSAR Measurements to Discriminate Among Mangrove Species

In this article, a polarimetric synthetic aperture radar (PolSAR) feature is analyzed to discriminate among different mangrove species. This feature, which is related to the Wishart distance, maximizes the contrast among mangrove species optimizing the ratio between quadratic forms. The discrimination performance is assessed both against ground truth and by intercomparing it with conventional model-based decomposition features. Results obtained by processing actual $L$ - and $C$ -band full-polarimetric synthetic aperture radar scenes collected by ALOS-PALSAR-2 and RADARSAT-2 missions show that the proposed approach achieves accurate enough discrimination performance to differentiate two out of the four mangrove species. In addition, results suggest using a multifrequency PolSAR approach to maximize discrimination performance

A dual-polarimetric approach to earthquake damage assessment

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

On the use of multipolarization satellite SAR data for coastline extraction in harsh coastal environments: the case of Solway Firth

This study deals with coastline extraction using multipolarization 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, 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 multipolarization information (either single- or dual-polarization metrics) and speckle filtering (either local and nonlocal approaches) are analyzed using global positioning system (GPS) samples and colocated 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, south-west 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 colocated GPS samples, show that: first, the multipolarization information outperforms the single-polarization counterpart in terms of extraction accuracy; second, among the single-polarization channels, the cross-polarized one performs best; third, both single- and dual-polarization methods perform better when nonlocal speckle filtering is applied; fourth, the joint combination of nonlocal speckle filter and dual-polarization information provides the best accuracy; and finally, 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

A New Orbiting Deployable System for Small Satellite Observations for Ecology and Earth Observation

In this paper, we present several study cases focused on marine, oceanographic, and atmospheric environments, which would greatly benefit from the use of a deployable system for small satellite observations. As opposed to the large standard ones, small satellites have become an effective and affordable alternative access to space, owing to their lower costs, innovative design and technology, and higher revisiting times, when launched in a constellation configuration. One of the biggest challenges is created by the small satellite instrumentation working in the visible (VIS), infrared (IR), and microwave (MW) spectral ranges, for which the resolution of the acquired data depends on the physical dimension of the telescope and the antenna collecting the signal. In this respect, a deployable payload, fitting the limited size and mass imposed by the small satellite architecture, once unfolded in space, can reach performances similar to those of larger satellites. In this study, we show how ecology and Earth Observations can benefit from data acquired by small satellites, and how they can be further improved thanks to deployable payloads. We focus on DORA—Deployable Optics for Remote sensing Applications—in the VIS to TIR spectral range, and on a planned application in the MW spectral range, and we carry out a radiometric analysis to verify its performances for Earth Observation studies

Multi-Polarization Methods to Detect Damages Related to Earthquakes

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

Towards ontology-enabled BioContexts for bioinformatics research

The evolution of web technologies seems to characterize a new scenario for biomedical researchers who take advantage from sophisticated ontologies offered by scientific portals. This paper introduces the concept of BioContext, a software environment which combines services for the fully exploitation of several ontologies whose knowledge is captured, and managed in a local repository. We illustrate our ideas pragmatically by presenting BCnotes, a BioContext which enables the functional annotation of biomedical texts in order to discover important relationships among genes

Kolgomorov Smirnov test based approach for SAR automatic target recognition

Automatic Target Recognition (ATR) aims at detecting the presence and at recognizing the typology and the orientation of targets within a scenario, by using an unsupervised approach. In Syntethic Aperture Radar imaging this turns to be a difficult task due to the specific characteristics of clutter and background noise. Within this manuscript a new two-steps ATR algorithm based on Kolmogorov-Smirnov test is presented. The method has been tested on real MSTAR datasets showing interesting performances

On the ability of dual-polarimetric SAR measurements to observe lava flows under different volcanic environments

In this study, we discuss the extra-value of polarimetric information in observing the lava flow. Dual-polarimetric Synthetic Aperture Radar (SAR) measurements are processed using a polarimetric change detector that, instead of looking at the variation of the backscatter intensity between a pair of images collected before and after the event, looks at changes in the polarimetric scattering behavior. We demonstrate that the scattering changes detected by the proposed polarimetric approach well-correlate with the footprint of the lava flow provided by external sources. In addition, we also compare the performance of the polarimetric change detector with conventional single-polarization metrics showing that the former one always outperforms the incoherent single-polarization measurements. To further demonstrate the robustness of the polarimetric change detectors, we selected two test cases that refer to vulcanic eruptions calling for completely different environments. The first one, related to the Etna volcano, calls for a lava flow over a vegetation-free environment; the second one is related to the Nyiragongo volcano and calls for a lava flow in a vegetated environment. Experimental results show that the polarimetric change detectors automatically adapt to the changing environment outperforming the single-polarization detectors

Monitoring Harsh Coastal Environments Using Polarimetric Sar Data: The Case of Solway Firth Wetlands

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