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27 pages, 5697 KiB  
Review
Optical Non-Invasive Glucose Monitoring Using Aqueous Humor: A Review
by Haolan Xi and Yiqing Gong
Sensors 2025, 25(13), 4236; https://doi.org/10.3390/s25134236 - 7 Jul 2025
Viewed by 705
Abstract
This review explores optical technologies for non-invasive glucose monitoring (NIGM) using aqueous humor (AH) as media, addressing the limitations of traditional invasive methods in diabetes management. It analyzes key techniques such as Raman spectroscopy, polarimetry, and mid- and near-infrared spectral methods, highlighting their [...] Read more.
This review explores optical technologies for non-invasive glucose monitoring (NIGM) using aqueous humor (AH) as media, addressing the limitations of traditional invasive methods in diabetes management. It analyzes key techniques such as Raman spectroscopy, polarimetry, and mid- and near-infrared spectral methods, highlighting their respective challenges, alongside emerging hybrid approaches like photoacoustic spectroscopy and optical coherence tomography. Crucially, the practical realization of these optical methods for portable NIGM hinges on advanced instrumentation. Therefore, this review also details progress in compact NIR spectrometers. While conventional systems often lack suitability, significant advancements in on-chip technologies—including miniaturized dispersive spectrometers and various on-chip Fourier transform systems (e.g., spatial heterodyne, stationary wave integral, and temporally modulated FT systems)—utilizing integration platforms like SOI and SiN are promising. Such innovations offer the potential for high spectral resolution, large bandwidth, and miniaturization, which are essential for developing practical AH-based NIGM systems to improve diabetes care. Full article
(This article belongs to the Special Issue Advances in Miniaturization and Power Efficiency of Optical Sensors)
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36 pages, 6489 KiB  
Article
Improving SAR Ship Detection Accuracy by Optimizing Polarization Modes: A Study of Generalized Compact Polarimetry (GCP) Performance
by Guo Song, Yunkai Deng, Heng Zhang, Xiuqing Liu and Sheng Chang
Remote Sens. 2025, 17(11), 1951; https://doi.org/10.3390/rs17111951 - 5 Jun 2025
Viewed by 750
Abstract
The debate surrounding the optimal polarimetric modes—compact polarimetry (CP) versus dual polarization (DP)—for PolSAR ship detection persists. This study pioneers a systematic investigation into Generalized Compact Polarimetry (GCP) for this application. By synthesizing and evaluating 143 distinct GCP configurations from fully polarimetric data, [...] Read more.
The debate surrounding the optimal polarimetric modes—compact polarimetry (CP) versus dual polarization (DP)—for PolSAR ship detection persists. This study pioneers a systematic investigation into Generalized Compact Polarimetry (GCP) for this application. By synthesizing and evaluating 143 distinct GCP configurations from fully polarimetric data, this study presents the first comprehensive comparison of their ship detection performance against conventional modes using Target-to-Clutter Ratio (TCR) and deep learning-based accuracy (AP50). Experiments on the FPSD dataset reveal that an optimized GCP mode (e.g., ellipse/orientation: [−10, −5]) consistently outperforms traditional CP and DP modes, yielding TCR gains of 0.2–2.7 dB. This translates to AP50 improvements of 0.5–4.7% (Faster R-CNN) and 0.1–5.5% (RetinaNet) over five common baseline modes. Crucially, this enhancement arises from optimizing the interaction between the polarization mode and target/clutter scattering characteristics rather than algorithmic improvements, supporting the proposed “optimization from the information source” strategy. These findings offer significant implications for future PolSAR system design and operational mode selection. Full article
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19 pages, 31258 KiB  
Article
Pyramid Fine and Coarse Attentions for Land Cover Classification from Compact Polarimetric SAR Imagery
by Saeid Taleghanidoozdoozan, Linlin Xu and David A. Clausi
Remote Sens. 2025, 17(3), 367; https://doi.org/10.3390/rs17030367 - 22 Jan 2025
Cited by 1 | Viewed by 809
Abstract
Land cover classification from compact polarimetry (CP) imagery captured by the launched RADARSAT Constellation Mission (RCM) is important but challenging due to class signature ambiguity issues and speckle noise. This paper presents a new land cover classification method to improve the learning of [...] Read more.
Land cover classification from compact polarimetry (CP) imagery captured by the launched RADARSAT Constellation Mission (RCM) is important but challenging due to class signature ambiguity issues and speckle noise. This paper presents a new land cover classification method to improve the learning of discriminative features based on a novel pyramid fine- and coarse-grained self-attention transformer (PFC transformer). The fine-grained dependency inside a non-overlapping window and coarse-grained dependencies between non-overlapping windows are explicitly modeled and concatenated using a learnable linear function. This process is repeated in a hierarchical manner. Finally, the output of each stage of the proposed method is spatially reduced and concatenated to take advantage of both low- and high-level features. Two high-resolution (3 m) RCM CP SAR scenes are used to evaluate the performance of the proposed method and compare it to other state-of-the-art deep learning methods. The results show that the proposed approach achieves an overall accuracy of 93.63%, which was 4.83% higher than the best comparable method, demonstrating the effectiveness of the proposed approach for land cover classification from RCM CP SAR images. Full article
(This article belongs to the Topic Computer Vision and Image Processing, 2nd Edition)
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15 pages, 1308 KiB  
Review
Considerations on Possible Directions for a Wide Band Polarimetry X-ray Mission
by Paolo Soffitta, Enrico Costa, Nicolas De Angelis, Ettore Del Monte, Klaus Desch, Alessandro Di Marco, Giuseppe Di Persio, Sergio Fabiani, Riccardo Ferrazzoli, Markus Gruber, Takahashi Hiromitsu, Saba Imtiaz, Philip Kaaret, Jochen Kaminski, Dawoon E. Kim, Fabian Kislat, Henric Krawczynski, Fabio La Monaca, Carlo Lefevre, Hemanth Manikantan, Herman L. Marshall, Romana Mikusincova, Alfredo Morbidini, Fabio Muleri, Stephen L. O’Dell, Takashi Okajima, Mark Pearce, Vladislavs Plesanovs, Brian D. Ramsey, Ajay Ratheesh, Alda Rubini, Shravan Vengalil Menon and Martin C. Weisskopfadd Show full author list remove Hide full author list
Galaxies 2024, 12(4), 47; https://doi.org/10.3390/galaxies12040047 - 8 Aug 2024
Viewed by 1613
Abstract
The Imaging X-ray Polarimetry Explorer (IXPE) has confirmed that X-ray polarimetry is a valuable tool in astronomy, providing critical insights into the emission processes and the geometry of compact objects. IXPE was designed to be sensitive in the 2–8 keV energy range for [...] Read more.
The Imaging X-ray Polarimetry Explorer (IXPE) has confirmed that X-ray polarimetry is a valuable tool in astronomy, providing critical insights into the emission processes and the geometry of compact objects. IXPE was designed to be sensitive in the 2–8 keV energy range for three primary reasons: (1) celestial X-ray sources are bright within this range, (2) the optics are effective, and (3) most sources across various classes were expected to exhibit some level of polarization. Indeed, IXPE is a great success, and its discoveries are necessitating the revision of many theoretical models for numerous sources. However, one of IXPE’s main limitations is its relatively narrow energy band, coupled with rapidly declining efficiency. In this paper, we will demonstrate the benefits of devising a mission focused on a broader energy band (0.1–79 keV). This approach leverages current technologies that align well with theoretical expectations and builds on the successes of IXPE. Full article
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13 pages, 2320 KiB  
Article
Optimizing Soil Moisture Retrieval: Utilizing Compact Polarimetric Features with Advanced Machine Learning Techniques
by Mohammed Dabboor, Ghada Atteia and Rana Alnashwan
Land 2023, 12(10), 1861; https://doi.org/10.3390/land12101861 - 29 Sep 2023
Cited by 3 | Viewed by 1650
Abstract
Soil moisture plays a crucial role in various environmental processes and is essential for agricultural management, hydrological modeling, and climate studies. Synthetic Aperture Radar (SAR) remote sensing presents significant potential for estimating soil moisture due to its ability to operate in all weather [...] Read more.
Soil moisture plays a crucial role in various environmental processes and is essential for agricultural management, hydrological modeling, and climate studies. Synthetic Aperture Radar (SAR) remote sensing presents significant potential for estimating soil moisture due to its ability to operate in all weather conditions and provide day-and-night imaging capabilities. Among the SAR configurations, the Compact Polarimetric (CP) mode has gained increasing interest as it relaxes system constraints, improves coverage, and enhances target information compared to conventional dual polarimetric SAR systems. This paper introduces a novel approach for soil moisture retrieval utilizing machine learning algorithms and CP SAR features. The CP SAR features are derived from a series of RADARSAT Constellation Mission (RCM) CP SAR imagery acquired over Canadian experimental sites equipped with Real-Time In Situ Soil Monitoring for Agriculture (RISMA) stations. This study employs a diverse dataset of compact polarimetric SAR features and corresponding ground truth soil moisture measurements for training and validation purposes. The results of our study achieved a Root Mean Square Error (RMSE) of 6.88% with a coefficient of determination R2 equal to 0.60, which corresponds to a correlation R between true and predicted soil moisture values of 0.75, using optimized Ensemble Learning Regression (ELR) with a decision-tree-based model. These results improved, yielding an RMSE of 5.67% and an R2 equal to 0.73 (R = 0.85), using an optimized Gaussian Process Regression (GPR) model. Full article
(This article belongs to the Topic Advances in Earth Observation and Geosciences)
(This article belongs to the Section Land – Observation and Monitoring)
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14 pages, 8911 KiB  
Article
Characterization of Chiral Nanostructured Surfaces Made via Colloidal Lithography
by Sabine Portal, Carles Corbella, Oriol Arteaga, Alexander Martin, Trinanjana Mandal and Bart Kahr
Nanomaterials 2023, 13(15), 2235; https://doi.org/10.3390/nano13152235 - 2 Aug 2023
Cited by 1 | Viewed by 1700
Abstract
Optically anisotropic materials were produced via colloidal lithography and characterized using scanning electronic microscopy (SEM), confocal microscopy, and polarimetry. A compact hexagonal array mask composed of silica sub-micron particles was fabricated via the Langmuir–Blodgett self-assembly technique. Subsequently, the mask pattern was transferred onto [...] Read more.
Optically anisotropic materials were produced via colloidal lithography and characterized using scanning electronic microscopy (SEM), confocal microscopy, and polarimetry. A compact hexagonal array mask composed of silica sub-micron particles was fabricated via the Langmuir–Blodgett self-assembly technique. Subsequently, the mask pattern was transferred onto monocrystalline silicon and commercial glass substrates using ion beam etching in a vacuum. Varying the azimuthal angle while etching at oblique incidence carved screw-like shaped pillars into the substrates, resulting in heterochiral structures depending on the azimuthal angle direction. To enhance the material’s optical properties through plasmon resonance, gold films were deposited onto the pillars. Polarimetric measurements were realized at normal and oblique incidences, showing that the etching directions have a clear influence on the value of the linear birefringence and linear dichroism. The polarimetric properties, especially the chiroptical responses, increased with the increase in the angle of incidence. Full article
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15 pages, 6296 KiB  
Technical Note
Region-Based Sea Ice Mapping Using Compact Polarimetric Synthetic Aperture Radar Imagery with Learned Features and Contextual Information
by Saeid Taleghanidoozdoozan, Linlin Xu and David A. Clausi
Remote Sens. 2023, 15(12), 3199; https://doi.org/10.3390/rs15123199 - 20 Jun 2023
Cited by 1 | Viewed by 2021
Abstract
Operational sea ice maps are usually generated manually using dual-polarization (DP) synthetic aperture radar (SAR) satellite imagery, but there is strong interest in automating this process. Recently launched satellites offer compact polarimetry (CP) imagery that provides more comprehensive polarimetric information compared to DP, [...] Read more.
Operational sea ice maps are usually generated manually using dual-polarization (DP) synthetic aperture radar (SAR) satellite imagery, but there is strong interest in automating this process. Recently launched satellites offer compact polarimetry (CP) imagery that provides more comprehensive polarimetric information compared to DP, which compels the use of CP for automated classification of SAR sea ice imagery. Existing sea ice scene classification algorithms using CP imagery rely on handcrafted features, while neural networks offer the potential of features that are more discriminating. We have developed a new and effective sea ice classification algorithm that leverages the nature of CP data. First, a residual-based convolutional neural network (ResCNN) is implemented to classify each pixel. In parallel, an unsupervised segmentation is performed to generate regions based on CP statistical properties. Regions are assigned a single class label by majority voting using the ResCNN output. For testing, quad-polarimetric (QP) SAR sea ice scenes from the RADARSAT Constellation Mission (RCM) are used, and QP, DP, CP, and reconstructed QP modes are compared for classification accuracy, while also comparing them to other classification approaches. Using CP achieves an overall accuracy of 96.86%, which is comparable to QP (97.16%), and higher than reconstructed QP and DP data by about 2% and 10%, respectively. The implemented algorithm using CP imagery provides an improved option for automated sea ice mapping. Full article
(This article belongs to the Section Ocean Remote Sensing)
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10 pages, 7209 KiB  
Communication
Design of Full Stokes Vector Polarimetry Based on Metasurfaces for Wide-Angle Incident Light
by Songjie Liu, Zejun Zhang, Jingxuan Cheng, Xiyin Wang, Shixiao Sun and Jing Xu
Photonics 2023, 10(4), 382; https://doi.org/10.3390/photonics10040382 - 30 Mar 2023
Cited by 2 | Viewed by 2211
Abstract
Polarization measurement plays an important role in optical detection, communication, and imaging systems. Compact polarimetry with a wide angle of incident light will break the restrictions of the limited incident angle and improve its practicality. In this paper, a full Stokes vector polarimetry [...] Read more.
Polarization measurement plays an important role in optical detection, communication, and imaging systems. Compact polarimetry with a wide angle of incident light will break the restrictions of the limited incident angle and improve its practicality. In this paper, a full Stokes vector polarimetry with a wide incident angle of ±20°, based on a two-dimensional metasurface, is proposed. According to the simulation results, the maximum measurement error of the Stokes vector at 20° oblique incidence is 0.09. The light transmittance of the proposed structure is higher than 83%. Moreover, the tilt angle of the incident light can be determined with a calculation error lower than 0.5°, according to the focusing position of the transmitted light on the focal plane. The operating wavelength of the proposed polarimetry is set to 530 nm of green light, which makes it a potential application in visible light communication and underwater optical systems. Full article
(This article belongs to the Special Issue Metasurface Diffraction and Polarization Optics)
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20 pages, 24131 KiB  
Article
A Refined Model for Quad-Polarimetric Reconstruction from Compact Polarimetric Data
by Rui Guo, Xiaopeng Zhao, Bo Zang, Yi Liang, Jian Bai and Liang Guo
Remote Sens. 2022, 14(20), 5226; https://doi.org/10.3390/rs14205226 - 19 Oct 2022
Cited by 2 | Viewed by 2009
Abstract
As a special dual-polarization technique, compact polarimetric (CP) synthetic aperture radar (SAR) has already been widely studied and installed on some spaceborne systems due to its superiority to quad-polarization; moreover, quad-pol information can be explored and reconstructed from the CP SAR data. In [...] Read more.
As a special dual-polarization technique, compact polarimetric (CP) synthetic aperture radar (SAR) has already been widely studied and installed on some spaceborne systems due to its superiority to quad-polarization; moreover, quad-pol information can be explored and reconstructed from the CP SAR data. In this paper, a refined model is proposed to estimate the quad-pol information for the CP mode. This model involves CP decomposition, wherein the polarization degree is introduced as the volume scattering model parameter. Moreover, a power-weighted model for the co-polarized coherence coefficient is proposed to avoid the iterative approach in pseudo-quad-pol information reconstruction. Experiments were implemented on the simulated Gaofen-3 and ALOS-2 data collected over San Francisco. Compared with typical reconstruction models, the proposed refined model shows its superiority in estimating the quad-pol information. Furthermore, terrain classification experiments using a complex-value convolutional neural network (CV-CNN) were performed on AIRSAR Flevoland data to validate the reconstruction effectiveness for classification applications. Full article
(This article belongs to the Special Issue SAR Images Processing and Analysis)
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17 pages, 8426 KiB  
Article
Polarimetry for 3He Ion Beams from Laser–Plasma Interactions
by Chuan Zheng, Pavel Fedorets, Ralf Engels, Chrysovalantis Kannis, Ilhan Engin, Sören Möller, Robert Swaczyna, Herbert Feilbach, Harald Glückler, Manfred Lennartz, Heinz Pfeifer, Johannes Pfennings, Claus M. Schneider, Norbert Schnitzler, Helmut Soltner and Markus Büscher
Instruments 2022, 6(4), 61; https://doi.org/10.3390/instruments6040061 - 10 Oct 2022
Cited by 2 | Viewed by 2155
Abstract
We present a compact polarimeter for 3He ions with special emphasis on the analysis of short-pulsed beams accelerated during laser–plasma interactions. We discuss the specific boundary conditions for the polarimeter, such as the properties of laser-driven ion beams, the selection of the [...] Read more.
We present a compact polarimeter for 3He ions with special emphasis on the analysis of short-pulsed beams accelerated during laser–plasma interactions. We discuss the specific boundary conditions for the polarimeter, such as the properties of laser-driven ion beams, the selection of the polarization-sensitive reaction in the polarimeter, the representation of the analyzing-power contour map, the choice of the detector material used for particle identification, as well as the production procedure of the required deuterated foil-targets. The assembled polarimeter has been tested using a tandem accelerator delivering unpolarized 3He ion beams, demonstrating good performance in the few-MeV range. The statistical accuracy and the deduced figure-of-merit of the polarimetry are discussed, including the count-rate requirement and the lower limit of accuracy for beam-polarization measurements at a laser-based ion source. Full article
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19 pages, 7823 KiB  
Article
The RADARSAT Constellation Mission Core Applications: First Results
by Mohammed Dabboor, Ian Olthof, Masoud Mahdianpari, Fariba Mohammadimanesh, Mohammed Shokr, Brian Brisco and Saeid Homayouni
Remote Sens. 2022, 14(2), 301; https://doi.org/10.3390/rs14020301 - 10 Jan 2022
Cited by 21 | Viewed by 6519
Abstract
The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture radar (SAR) meets the expectations of intended users. In this [...] Read more.
The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture radar (SAR) meets the expectations of intended users. In this study, we provide an overview of initial results obtained for three high-priority applications; flood mapping, sea ice analysis, and wetland classification. In our study, the focus is on results obtained using not only linear polarization, but also the adopted Compact Polarimetric (CP) architecture in RCM. Our study shows a promising level of agreement between RCM and RADARSAT-2 performance in flood mapping using dual-polarized HH-HV SAR data over Red River, Manitoba, suggesting smooth continuity between the two satellite missions for operational flood mapping. Visual analysis of coincident RCM CP and RADARSAT-2 dual-polarized HH-HV SAR imagery over the Resolute Passage, Canadian Central Arctic, highlighted an improved contrast between sea ice classes in dry ice winter conditions. A statistical analysis using selected sea ice samples confirmed the increased contrast between thin and both rough and deformed ice in CP SAR. This finding is expected to enhance Canadian Ice Service’s (CIS) operational visual analysis of sea ice in RCM SAR imagery for ice chart production. Object-oriented classification of a wetland area in Newfoundland and Labrador by fusion of RCM dual-polarized VV-VH data and Sentinel-2 optical imagery revealed promising classification results, with an overall accuracy of 91.1% and a kappa coefficient of 0.87. Marsh presented the highest user’s and producer’s accuracies (87.77% and 82.08%, respectively) compared to fog, fen, and swamp. Full article
(This article belongs to the Special Issue RADARSAT Constellation Mission (RCM))
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21 pages, 5854 KiB  
Article
Framework for Reconstruction of Pseudo Quad Polarimetric Imagery from General Compact Polarimetry
by Junjun Yin and Jian Yang
Remote Sens. 2021, 13(3), 530; https://doi.org/10.3390/rs13030530 - 2 Feb 2021
Cited by 8 | Viewed by 3656
Abstract
Pseudo quad polarimetric (quad-pol) image reconstruction from the hybrid dual-pol (or compact polarimetric (CP)) synthetic aperture radar (SAR) imagery is a category of important techniques for radar polarimetric applications. There are three key aspects concerned in the literature for the reconstruction methods, i.e., [...] Read more.
Pseudo quad polarimetric (quad-pol) image reconstruction from the hybrid dual-pol (or compact polarimetric (CP)) synthetic aperture radar (SAR) imagery is a category of important techniques for radar polarimetric applications. There are three key aspects concerned in the literature for the reconstruction methods, i.e., the scattering symmetric assumption, the reconstruction model, and the solving approach of the unknowns. Since CP measurements depend on the CP mode configurations, different reconstruction procedures were designed when the transmit wave varies, which means the reconstruction procedures were not unified. In this study, we propose a unified reconstruction framework for the general CP mode, which is applicable to the mode with an arbitrary transmitted ellipse wave. The unified reconstruction procedure is based on the formalized CP descriptors. The general CP symmetric scattering model-based three-component decomposition method is also employed to fit the reconstruction model parameter. Finally, a least squares (LS) estimation method, which was proposed for the linear π/4 CP data, is extended for the arbitrary CP mode to estimate the solution of the system of non-linear equations. Validation is carried out based on polarimetric data sets from both RADARSAT-2 (C-band) and ALOS-2/PALSAR (L-band), to compare the performances of reconstruction models, methods, and CP modes. Full article
(This article belongs to the Section Remote Sensing Image Processing)
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20 pages, 5359 KiB  
Review
Hybrid Compact Polarimetric SAR for Environmental Monitoring with the RADARSAT Constellation Mission
by Brian Brisco, Masoud Mahdianpari and Fariba Mohammadimanesh
Remote Sens. 2020, 12(20), 3283; https://doi.org/10.3390/rs12203283 - 9 Oct 2020
Cited by 50 | Viewed by 5149
Abstract
Canada’s successful space-based earth-observation (EO) radar program has earned widespread and expanding user acceptance following the launch of RADARSAT-1 in 1995. RADARSAT-2, launched in 2007, while providing data continuity for its predecessor’s imaging capabilities, added new polarimetric modes. Canada’s follow-up program, the RADARSAT [...] Read more.
Canada’s successful space-based earth-observation (EO) radar program has earned widespread and expanding user acceptance following the launch of RADARSAT-1 in 1995. RADARSAT-2, launched in 2007, while providing data continuity for its predecessor’s imaging capabilities, added new polarimetric modes. Canada’s follow-up program, the RADARSAT Constellation Mission (RCM), launched in 2019, while providing continuity for its two predecessors, includes an innovative suite of polarimetric modes. In an effort to make polarimetry accessible to a wide range of operational users, RCM uses a new method called hybrid compact polarization (HCP). There are two essential elements to this approach: (1) transmit only one polarization, circular; and (2) receive two orthogonal polarizations, for which RCM uses H and V. This configuration overcomes the conventional dual and full polarimetric system limitations, which are lacking enough polarimetric information and having a small swath width, respectively. Thus, HCP data can be considered as dual-pol data, while the resulting polarimetric classifications of features in an observed scene are of comparable accuracy as those derived from the traditional fully polarimetric (FP) approach. At the same time, RCM’s HCP methodology is applicable to all imaging modes, including wide swath and ScanSAR, thus overcoming critical limitations of traditional imaging radar polarimetry for operational use. The primary image data products from an HCP radar are different from those of a traditional polarimetric radar. Because the HCP modes transmit circularly polarized signals, the data processing to extract polarimetric information requires different approaches than those used for conventional linearly polarized polarimetric data. Operational users, as well as researchers and students, are most likely to achieve disappointing results if they work with traditional polarimetric processing tools. New tools are required. Existing tutorials, older seminar notes, and reference papers are not sufficient, and if left unrevised, could succeed in discouraging further use of RCM polarimetric data. This paper is designed to provide an initial response to that need. A systematic review of studies that used HCP SAR data for environmental monitoring is also provided. Based on this review, HCP SAR data have been employed in oil spill monitoring, target detection, sea ice monitoring, agriculture, wetland classification, and other land cover applications. Full article
(This article belongs to the Special Issue Environmental Mapping Using Remote Sensing)
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23 pages, 7233 KiB  
Article
Compact Polarimetry Response to Modeled Fast Sea Ice Thickness
by Mohammed Dabboor and Mohammed Shokr
Remote Sens. 2020, 12(19), 3240; https://doi.org/10.3390/rs12193240 - 5 Oct 2020
Cited by 9 | Viewed by 2998
Abstract
Compact Polarimetric (CP) Synthetic Aperture Radar (SAR) is expected to gain more and more ground for Earth observation applications in the coming years. This comes in light of the recently launched RADARSAT Constellation Mission (RCM), which uniquely provides CP SAR imagery in operational [...] Read more.
Compact Polarimetric (CP) Synthetic Aperture Radar (SAR) is expected to gain more and more ground for Earth observation applications in the coming years. This comes in light of the recently launched RADARSAT Constellation Mission (RCM), which uniquely provides CP SAR imagery in operational mode. In this study, we present observations about the sensitivity of CP SAR imagery to thickness of thermodynamically-grown fast sea ice during early ice growth (September–December 2017) in the Resolute Bay area, Canadian Central Arctic. Fast ice is most suitable to use for this preliminary study since it exhibits only thermodynamic growth in absence of ice mobility and deformation. Results reveal that ice thickness up to 30 cm can be retrieved using several CP parameters from the tested set. This ice thickness corresponds to the thickness of young ice. We found the surface scattering mechanism to be dominant during the early ice growth, exposing an increasing tendency up to 30 cm thickness with a correlation coefficient with the thickness equal to 0.86. The degree of polarization was found to be the parameter with the highest correlation up to 0.95. While thickness retrieval within the same range is also possible using parameters from Full Polarimetric (FP) SAR parameters as shown in previous studies, the advantage of using CP SAR mode is the much larger swath coverage, which is an operational requirement. Full article
(This article belongs to the Special Issue RADARSAT Constellation Mission (RCM))
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19 pages, 10961 KiB  
Article
Investigation of C-Band SAR Polarimetry for Mapping a High-Tidal Coastal Environment in Northern Canada
by Khalid Omari, René Chenier, Ridha Touzi and Mesha Sagram
Remote Sens. 2020, 12(12), 1941; https://doi.org/10.3390/rs12121941 - 16 Jun 2020
Cited by 12 | Viewed by 3116
Abstract
Synthetic Aperture Radar (SAR) has been used in characterizing intertidal zones along northern Canadian coastlines. RADARSAT-2, with its full polarimetric information, has been considered for monitoring these vulnerable ecosystems and helping enhance the navigational safety of these waters. The RADARSAT Constellation Mission (RCM) [...] Read more.
Synthetic Aperture Radar (SAR) has been used in characterizing intertidal zones along northern Canadian coastlines. RADARSAT-2, with its full polarimetric information, has been considered for monitoring these vulnerable ecosystems and helping enhance the navigational safety of these waters. The RADARSAT Constellation Mission (RCM) will ensure data continuity with three identical SAR satellites orbiting together, providing superior revisit capabilities. The three satellites are equipped with multiple configurations, including single-polarization (HH, HV, VV), conventional (HH-HV, VV-VH, and HH-VV), hybrid (i.e., compact) dual polarization, and fully polarimetric (FP) modes. This study investigates the potential of the compact polarimetric (CP) mode for mapping an intertidal zone located at Tasiujaq village on the southwest shore of Ungava Bay, Quebec. Simulated RCM data were generated using FP RADARSAT-2 images collected over the study site in 2016. Commonly used tools for CP analysis include Raney m-delta classification and the hybrid dual polarizations RH-RV (where the transmitter is right-circular and the receivers are horizontal and vertical linear polarizations) and RR-RL (where the transmitter is right circular and the receivers are right-circular and left-circular polarizations). The potential of CP is compared with single, conventional dual-pol, and FP. The Freeman–Durden and Touzi discriminators are used for FP analysis. The random forest classifier is used as a classification approach due to its well-documented performance compared to other classifiers. The results suggest that the hybrid compact (RR-RL and RH-RV) dual polarizations provide encouraging separability capacities with overall accuracies of 61% and 60.7%, respectively, although they do not perform as well as conventional dual-pol HH-HV (64.4%). On the other hand, the CP polarimetric m-delta decomposition generated slightly less accurate classification results with an overall accuracy of approximately 62% compared to the FP Freeman–Durden (67.08%) and Touzi discriminators (71.1%). Full article
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