Quad-pol Synthetic Aperture Radar Research Articles

Polarization Dependence of Azimuth Cutoff From Quad-Pol SAR Images

Although basic understanding of the synthetic aperture radar (SAR) imaging mechanism of ocean waves has been achieved, challenges still remain. In this paper, a large number of quad-polarized SAR images are analyzed to help assess how the standard SAR imaging transformation applies to all polarization channels. Foremost, the azimuth cutoff, a parameter essentially governed by the detected wave motions, is today solely related to radar configuration and the ocean wave spectrum but not to the polarization configuration. As obtained, the analyses based on quad-polarized Radarsat-2 and Gaofen-3 products document the distinct dependence of azimuth cutoff on polarization and incidence angle. Especially for cross-polarized VH measurements, azimuth cutoff estimates are generally larger than copolarized HH ones, the latter already being larger than values estimated under VV configuration. This trend increases with the incidence angle. The systematic comparisons between SAR measurements and simulations further demonstrate that the present SAR nonlinear transformation may not properly take into account the differing coherence time associated with the multi-polarized observation of ocean scenes. In particular, to reproduce the large azimuth cutoff parameters of cross-polarized images, a reduced coherence time shall be expected. This measurable sensitivity shall enhance the capabilities of polarized SAR systems to precisely derive more ocean surface properties, especially the influence of wave breakers, by combining both the copolarization and cross-polarization measurements.

On Quad-Polarized SAR Measurements of the Ocean Surface

This paper provides improved quantitative estimates of the wind-ruffled roughness contributions to dual co- and cross-polarized radar signals. Expanding previous approaches, 1696 RADARSAT-2 quad-polarized synthetic aperture radar (SAR) measurements, co-located with 65 in situ National Data Buoy Center (NDBC) buoy observations, are analyzed. Considering all wind conditions, the impact of breaking and near-breaking waves on dual co- and cross-polarized radar signals is robustly documented. For VV polarized measurements, the contribution of breaking waves decreased from 60% to 20% with increasing incidence angle, whereas for HH polarization and cross-polarization measurements, it can amount to about 60%–70% for all incidence angles. Building on the large analyzed data set, robust empirical dependencies between breaking waves and their impact on co- and cross-pol signals are then derived, as functions of wind speeds, incidence angles, and azimuth directions.

On C-Band Quad-Polarized Synthetic Aperture Radar Properties of Ocean Surface Currents

We present new results for ocean surface current signatures in dual co- and cross-polarized synthetic aperture radar (SAR) images. C-band RADARSAT-2 quad-polarized SAR ocean scenes are decomposed into resonant Bragg scattering from regular (non-breaking) surface waves and scattering from breaking waves. Surface current signatures in dual co- and cross-polarized SAR images are confirmed to be governed by the modulations due to wave breaking. Due to their small relaxation scale, short Bragg waves are almost insensitive to surface currents. Remarkably, the contrast in sensitivity of the non-polarized contribution to dual co-polarized signals is found to largely exceed, by a factor of about 3, the contrast in sensitivity of the corresponding cross-polarized signals. A possible reason for this result is the co- and cross-polarized distinct scattering mechanisms from breaking waves: for the former, quasi-specular radar returns are dominant, whereas for the latter, quasi-resonant scattering from the rough breaking crests governs the backscatter intensity. Thus, the differing sensitivity can be related to distinct spectral intervals of breaking waves contributing to co- and cross-polarized scattering in the presence of surface currents. Accordingly, routinely observed current signatures in quad-polarized SAR images essentially originate from wave breaking modulations, and polarized contrasts can therefore help quantitatively retrieve the strength of surface current gradients.

Detection and Velocity Measurement of Brash Ice in the Arctic Ocean by TerraSAR-X Quad-pol SAR

Hong, S.H.; Kim, J.H.; Park, J.W., and Won, J.S., 2019. Detection and velocity measurement of brash ice in the Arctic Ocean by TerraSAR-X quad-pol SAR. In: Jung, H.S.; Lee, S.; Ryu, J.H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 1–10. Coconut Creek (Florida), ISSN 0749-0208.A new method is presented using a TerraSAR-X quad-pol synthetic aperture radar (SAR) observation for detection and velocity measurement of sea ice drift, which can be useful information to improve sea ice models in the Arctic and Antarctic Oceans. It is very difficult to detect and measure slow moving natural objects using only a space-borne SAR observation without any terrestrial measurement. The core idea is to exploit a slight time difference between different polarizations (i.e., H- and V-pol transmitted signals). The ground motion can be estimated by measuring the slope of residual Doppler frequency versus azimuth time difference without the knowledge of different scattering centers. The results demonstrate effective detection of the flow of brash ice. The SAR-measured velocities were approximately 0.2-0.3 m/s for ice floes and 1.4-3.5 m/s for brash ice flowing through ice fractures. The method was validated by using a pursuit monostatic TanDEM-X mode observation, by which two satellites observed the same sea ice with about a ten-second time interval. The sea ice velocities measured by the proposed approach using only one dataset well correlated with the results from offset tracking method applied to the two datasets with a correlation determination R2 of 0.93. The cross-pol (HV- and VH-pol) pair is more effective to measure the velocity because the scattering center distance decreases significantly in the cross-pol pair, and data with high coherence are required for velocity estimation.

C-Band Right-Circular Polarization Ocean Wind Retrieval

We report an investigation of ocean-surface wind speed retrieval from C-band RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) images using a new channel of coright-circular polarization (RR-pol) in compact polarimetry (CP) option. The analysis of simulated RCM quad-polarized CP SAR data and collocated in situ buoy measurements suggests that the RR-pol is much less sensitive to wind directions than the other three polarizations in the CP option. A method is proposed for the RR-pol radar signal as a function of wind speed and incidence angle. We demonstrate that C-band RR-pol has the potential for ocean high wind retrieval, especially for cyclone studies.

Preliminary Evaluation of Gaofen-3 Quad-Polarized SAR Imagery for Longbao Protected Plateau Wetland Reserve

The Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) satellite launched by the China Academy of Space Technology is under continuous operating mode at C-band since September 2016. The main objective of this study was to present a preliminary evaluation of GF-3 quad-polarized SAR imagery for protected wetland classification. Four scenes of GF-3 quad-polarized SAR imageries were collected in this study and analyzed systematically. Besides, the GF-2 optical imagery and in situ survey results were also collocated as reference data. It was verified that the polarized features including double bounce scattering component Pdbl, odd bounce scattering component Podd, and volume scattering component Pvol from Freeman decomposition algorithm were well applied in distinguishing typical coverage of Longbao protected plateau wetland. In consideration of robustness of classifier, the method of Maximum Likelihood Classification was investigated for classification based on selected polarized features. The Kappa coefficient and overall accuracy of classification mapping are 0.75 and 82.16%, respectively, which revealed that the GF-3 quad-polarized SAR can provide a satisfying mapping for classification of Longbao protected plateau wetland.

Soil Moisture Retrieval Using Quad-Polarized SAR Data from Radar Imaging Satellite 1 (RISAT1) Through Artificial Intelligence-Based Soft Computing Techniques

The present study aims to explore and compare the potential of different Artificial Intelligence-based Soft Computing (AISC) techniques to prepare surface Soil Moisture Content (SMC) map using fine-resolution (~ 5 m), quad-polarized Synthetic Aperture Radar (SAR) data obtained from Radar Imaging Satellite 1 (RISAT1). Potential of three different AISC techniques, i.e. Support Vector Machine (SVM), Random Forest (RF) and Genetic Programming (GP), is explored. The estimated surface SMC is validated with the field soil moisture values in both bare and vegetated lands (< 30 cm height). Different techniques have their own merits and demerits; however, we recommend GP to be most useful due to its other features. For example, GP provides the mathematical relationship, importance and sensitivity of each individual input to the surface SMC. This helps us to quantify the contribution of quad-polarized backscattering coefficients and soil texture information. It is noticed that the use of only SAR data without soil texture information may be acceptable with reasonable accuracy with an enormous benefit of its applicability to the locations without soil texture information. Using this, an exemplary fine-resolution (~ 5 m) SMC map is developed. Such high-resolution maps for large spatial extent are expected to be highly useful in many applications.

Hybrid Dual-Polarization Synthetic Aperture Radar

Compact polarimetry for a synthetic aperture radar (SAR) system is reviewed. Compact polarimetry (CP) is intended to provide useful polarimetric image classifications while avoiding the disadvantages of space-based quadrature-polarimetric (quad-pol) SARs. Two CP approaches are briefly described, π/4 and circular. A third form, hybrid compact polarimetry (HCP) has emerged as the preferred embodiment of compact polarimetry. HCP transmits circular polarization and receives on two orthogonal linear polarizations. When seen through its associated data processing and image classification algorithms, HPC’s heritage dates back to the Stokes parameters (1852), which are summarized and explained in plain language. Hybrid dual-polarimetric imaging radars were in the payloads of two lunar-orbiting satellites, India’s Earth-observing RISAT-1, and Japan’s ALOS-2. In lunar or planetary orbit, a satellite equipped with an HCP imaging radar delivers the same class of polarimetric information as Earth-based radar astronomy. In stark contrast to quad-pol, compact polarimetry is compatible with wide swath modes of a SAR, including ScanSAR. All operational modes of the SARs aboard Canada’s three-satellite Radarsat Constellation Mission (RCM) are hybrid dual-polarimetric. Image classification methodologies for HCP data are reviewed, two of which introduce errors for reasons explained. Their use is discouraged. An alternative and recommended group of methodologies yields reliable results, illustrated by polarimetrically classified images. A survey over numerous quantitative studies demonstrates HCP polarimetric classification effectiveness. The results verify that the performance accuracy of the HCP architecture is comparable to the accuracy delivered by a quadrature-polarized SAR. Four appendices are included covering related topics, including comments on inflight calibration of an HCP radar.

Estimation of rice yield from a C-band radar remote sensing image by integrating a physical scattering model and an optimization algorithm

Accurate estimation of rice yield with remotely sensed data plays a role in ensuring food security at local or national scales. In this study, an estimation scheme integrating a rice canopy scattering model (RCSM) and a genetic algorithm optimization tool (GAOT) was proposed on a basis of radar remote sensing technology. A C-band Radarsat-2 synthetic aperture radar (SAR) image acquired at rice maturity stage in Northeast, China was tested to simulate three yield-related rice parameters via an integrated RCSM-GAOT scheme, with a parallel computing environment. Rice yield was then estimated via a regression analysis by linking the simulated parameters to rice ear weights. Results showed that three parameters, ear length, ear diameter and ear density, can be simulated by the RCSM-GAOT scheme with a simulation error of 1.2 cm, 0.11 cm and 29 ears/m2, respectively. Rice yield is estimated with an average error of 0.28 kg/m2 and 0.22 kg/m2 for fresh ear weight and dry ear weight, respectively. In comparison with the need of multiple SAR data acquisitions in past studies, this study demonstrates the capability of one time Radarsat-2 quad-polarized SAR image in regional rice yield estimation. At the same time, it also indicates that the proposed RCSM-GAOT scheme has a potential in future precision agriculture applications.

Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation

ABSTRACTGroundwater assists farmers to irrigate crops for fulfilling the crop-water requirement. Indian agriculture system is characterized by three cropping seasons known as Kharif (monsoon), Rabi (post-monsoon) and summer (pre-monsoon). In tropical countries like India, monitoring cropping practices using optical remote sensing during Kharif and Rabi seasons is constraint due to the cloud cover, which can be well addressed by microwave remote sensing. In the proposed research, the strength of C-band polarimetric Synthetic Aperture Radar (SAR) time series images were evaluated to classify groundwater irrigated croplands for the Kharif and Rabi cropping seasons of the year 2013. The present study was performed in the Berambadi experimental watershed of Kabini river basin, southern peninsular India. A total of fifteen polarimetric variables were estimated includes four backscattering coefficients (HH, HV, VH, VV) and eleven polarimetric indices for all Radarsat-2 SAR images. The cumulative temporal sum (seasonal and dual-season) of these parameters was supervised classified using Support Vector Machine (SVM) classifier with intensive ground observation samples. Classification results using the best equation (highest accuracy and kappa) shows that the Kharif, Rabi and irrigated double croplands are respectively 9.58 km2 (20.6%), 16.14 km2 (34.7%) and 6.22 km2 (13.4%) with a kappa coefficient respectively 0.84, 0.74 and 0.94.

Modeling Multifrequency Pol-InSAR Data From the Percolation Zone of the Greenland Ice Sheet

The analysis of data from an airborne synthetic aperture radar (SAR) campaign in the percolation zone of Greenland revealed an interferometric coherence undulation behavior with respect to vertical wavenumber, which cannot be explained with existing models. We propose a model extension that accounts for scattering from distinct layers below the surface. Simulations show that the periodicity of the coherence undulation is mainly driven by the vertical distance between dominant subsurface layers, while the amplitude of the undulation is determined by the ratio between scattering from distinct layers and scattering from the firn volume. We use the model to interpret quad-pol SAR data at X-, C-, S-, L-, and P-bands. The inferred layer depths match layer detections in ground-based radar data and in situ measurements. We conclude that in the percolation zone, scattering from subsurface layers has to be taken into account to correctly interpret SAR data and demonstrate the potential to retrieve geophysical information about the vertical subsurface structure.

Potential of soil moisture retrieval for tropical peatlands in Indonesia using ALOS-2 L-band full-polarimetric SAR data

ABSTRACTIn this paper, a soil moisture retrieval from full-polarimetric synthetic aperture radar (SAR) data is investigated for sparsely vegetated soil surfaces. An improved retrieval method adapting the variations in vegetation is proposed by incorporating the generalized volume model into the polarimetric two-scale two-component model (PTSTCM). The feasibility of the method, termed as the adaptive PTSTCM, has been tested for tropical peatland sites in Indonesia which exhibit a variety of sparse vegetation cover on soil after land clearing activities. The data were collected in March and August 2017 with the time domain reflectometry (TDR) probe for a total of 18 sample points over 11 regions. The method was applied to ALOS-2 L-band quad-pol SAR data that were acquired simultaneously with field measurements. We compared the results between the proposed adaptive PTSTCM and the original PTSTCM that utilizes specific types of volume model (i.e., randomly, horizontally, and vertically oriented volume models). Scatterplots of estimated versus measured results reveal that the adaptive PTSTCM yields a root-mean-square error (RMSE) of 5.1vol. and inversion rate of 35.0 and 58.5 for March and August data, respectively, which are found to be superior to those of the original PTSTCM.

Ocean Wind Retrieval Models for RADARSAT Constellation Mission Compact Polarimetry SAR

We propose two new ocean wind retrieval models for right circular-vertical (RV) and right circular-horizontal (RH) polarizations respectively from the compact-polarimetry (CP) mode of the RADARSAT Constellation Mission (RCM), which is scheduled to be launched in 2019. For compact RV-polarization (right circular transmit and vertical receive), we build the wind retrieval model (denoted CoVe-Pol model) by employing the geophysical model function (GMF) framework and a sensitivity analysis. For compact RH polarization (right circular transmit and horizontal receive), we build the wind retrieval model (denoted the CoHo-Pol model) by using a quadratic function to describe the relationship between wind speed and RH-polarized normalized radar cross-sections (NRCSs) along with radar incidence angles. The parameters of the two retrieval models are derived from a database including wind vectors measured by in situ National Data Buoy Center (NDBC) buoys and simulated RV- and RH-polarized NRCSs and incidence angles. The RV- and RH-polarized NRCSs are generated by a RCM simulator using C-band RADARSAT-2 quad-polarized synthetic aperture radar (SAR) images. Our results show that the two new RCM CP models, CoVe-Pol and CoHo-POL, can provide efficient methodologies for wind retrieval.

COMBINED ANALYSIS OF RADARSAT-2 SAR AND SENTINEL-2 OPTICAL DATA FOR IMPROVED MONITORING OF TUBER INITIATION STAGE OF POTATO

Abstract. Tuber initiation and tuber bulking stages are critical part of various phenological phases for potato production. Tuber initiation covers the period from the formation of spherical rhizome ends, the flowering and the start of tuber bulking. In general, the tuberization spans from 3 to 5 weeks after emergence and ends with the row closer i.e. canopies in adjacent rows touch each other across the furrow. Hence, this rapid growth seeks critical agronomic management practices such as irrigation and fertilization. It majorly influences the growth of stems, foliar area, dry weight and number of tubers particularly at the phase of tuber initiation. During these phenological stages, potato crops are susceptible to the infestation of late blight diseases caused by Phytophthora infestans and largely affects the potato production. Thus identifying the crop risk using remote sensing approaches can provide an efficient potato growth monitoring framework. In the context of monitoring crop dynamics, quad-pol Synthetic Aperture Radar (SAR) data has proven to be effective due to its sensitivity towards dielectric and geometric properties. In addition to SAR data, optical remote sensing data derived vegetation information can provide an improved insight into crop growth when combined with SAR data. In this research, quad-pol RADARSAT-2 and Sentinel-2 optical data are analyzed to monitor potato tuberization phase over Bardhaman district in the state ofWest Bengal, which is one of the major potato growing regions in India. The proposed approach uses polarimetric parameters such as backscatter intensities, ratio (HH/VV, VH/VV, linear depolarization ratio), and co-pol correlation (ρHH–VV) along with the vegetation indices derived from the Sentinel-2 data for understanding the spatio-temporal dynamics. The initial results show a promising accuracy in monitoring the dynamics of potato tuberization. Integration of such earth observation (EO) data, in conjunction with in-situ field measurements, might significantly enhance the current capabilities for crop monitoring.

Mapping Mangrove Forests of Dongzhaigang Nature Reserve in China Using Landsat 8 and Radarsat-2 Polarimetric SAR Data

Mangrove forests are distributed in intertidal regions that act as a “natural barrier” to the coast. They have enormous ecological, economic, and social value. However, the world’s mangrove forests are declining under immense pressure from anthropogenic and natural disturbances. Accurate information regarding mangrove forests is essential for their protection and restoration. The main objective of this study was to develop a method to improve the classification of mangrove forests using C-band quad-pol Synthetic Aperture Radar (SAR) data (Radarsat-2) and optical data (Landsat 8), and to analyze the spectral and backscattering signatures of mangrove forests. We used a support vector machine (SVM) classification method to classify the land use in Hainan Dongzhaigang National Nature Reserve (HDNNR). The results showed that the overall accuracy using only optical information was 83.5%. Classification accuracy was improved to a varying extent by the addition of different radar data. The highest overall accuracy was 95.0% based on a combination of SAR and optical data. The area of mangrove forest in the reserve was found to be 1981.7 ha, as determined from the group with the highest classification accuracy. Combining optical data with SAR data could improve the classification accuracy and be significant for mangrove forest conservation.

Multifrequency and Full-Polarimetric SAR Assessment for Estimating Above Ground Biomass and Leaf Area Index in the Amazon Várzea Wetlands

The aim of this study is to evaluate the potential of multifrequency and Full-polarimetric Synthetic Aperture Radar (SAR) data for retrieving both Above Ground Biomass (AGB) and Leaf Area Index (LAI) in the Amazon floodplain forest environment. Two specific questions were proposed: (a) Does multifrequency SAR data perform more efficiently than single-frequency data in estimating LAI and AGB of várzea forests?; and (b) Are quad-pol SAR data more efficient than single- and dual-pol SAR data in estimating LAI and AGB of várzea forest? To answer these questions, data from different sources (TerraSAR-X Multi Look Ground Range Detected (MGD), Radarsat-2 Standard Qual-Pol, advanced land observing satellite (ALOS)/ phased-arrayed L-band SAR (PALSAR-1). Fine-beam dual (FDB) and quad Polarimetric mode) were combined in 10 different scenarios to model both LAI and AGB. A R-platform routine was implemented to automatize the selection of the best regression models. Results indicated that ALOS/PALSAR variables provided the best estimates for both LAI and AGB. Single-frequency L-band data was more efficient than multifrequency SAR. PALSAR-FDB HV-dB provided the best LAI estimates during low-water season. The best AGB estimates at high-water season were obtained by PALSAR-1 quad-polarimetric data. The top three features for estimating AGB were proportion of volumetric scattering and both the first and second dominant phase difference between trihedral and dihedral scattering, extracted from Van Zyl and Touzi decomposition, respectively. The models selected for both AGB and LAI were parsimonious. The Root Mean Squared Error (RMSEcv), relative overall RMSEcv (%) and R2 value for LAI were 0.61%, 0.55% and 13%, respectively, and for AGB, they were 74.6 t·ha−1, 0.88% and 46%, respectively. These results indicate that L-band (ALOS/PALSAR-1) has a high potential to provide quantitative and spatial information about structural forest attributes in floodplain forest environments. This potential may be extended not only with PALSAR-2 data but also to forthcoming missions (e.g., NISAR, Global Ecosystems Dynamics Investigation Lidar (GEDI), BIOMASS, Tandem-L) for promoting wall-to-wall AGB mapping with a high level of accuracy in dense tropical forest regions worldwide.

Full-polarimetric burn scar mapping – the differences of active fire and post-fire situations

ABSTRACTFire is a threat to human lives, infrastructure, and forestry. Satellite-based Earth observations enable a fast, efficient, and reliable estimation of burnt area. In most cases, optical satellite data are used for burn scar detection. However, smoke and cloud coverage strongly limits the suitability of optical imagery for rapid mapping of burn scars. Here, an automated procedure based on quad-polarized L-band Synthetic Aperture Radar (SAR) data is presented to enable fast burn scar mapping independently of the weather and smoke conditions. Full-polarimetric SAR data enable the decomposition of the SAR backscatter into different scattering mechanisms, describing the scatterer more precisely. Important differences in the polarimetric backscattering behaviour during the active fire and post-fire situations are reported. While the SPAN difference is best suited for burn scar mapping during active fire situations, the Entropy-Anisotropy-Alpha and the generalized Freeman–Durden decompositions showed the best suitability for burnt area mapping several months after the end of the fire. The proposed methodology is an object-based image analysis approach based on change detection. The big fire event which affected Fort McMurray, Alberta, Canada, in May–June 2016 was investigated as a case study.

Semi-empirical ocean surface model for compact-polarimetry mode SAR of RADARSAT Constellation Mission

A semi-empirical model of the ocean surface is developed for the compact-polarimetry (CP) mode of Synthetic Aperture Radar (SAR) which will be a main product of the RADARSAT Constellation Mission (RCM), scheduled for launch in November 2018. The fundamental mechanism for the semi-empirical model is the interactions between sea surface waves and the radar microwave. Sea surface waves are generated by ocean surface winds and may be modulated by precipitation or oceanic processes, such as surface currents, internal waves (IWs), and surfactants (e.g. oil spill, and sea ice). Model results for normalized radar cross sections (NRCSs) induced by ocean winds are validated against a database we developed. The ocean wind vectors were observed by in situ buoys of the National Data Buoy Center (NDBC); the RCM NRCSs are obtained from a “CP simulator”, using composites of RADARSAT-2 quad-pol SAR images. We simulate the dependencies of the NRCSs on wind speeds and incidence angles, for up-wind (wind direction is 0°) and cross-wind (wind direction is 90°) conditions. And we report the potential abilities and limitations of ocean winds monitoring using the RCM CP mode, as well as suggest that the RV-pol should be suitable for hurricane monitoring in the future. As hurricanes containing high winds are generally associated with heavy rain conditions, we discuss the possible mechanisms for precipitation effects related to the RV- and RH- polarizations by simulating two effects on the ocean surface waves. Moreover, we suggest that the RCM CP mode is better able to monitor the ocean surface currents than the fully polarimetry SAR systems (e.g. RADARSAT-2), because of the associated large swath and the possible continuous images of three RCM satellites.

A Preliminary Analysis of Wind Retrieval, Based on GF-3 Wave Mode Data.

This paper presents an analysis of measurements of the normalized radar cross-(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, this experiment verifies the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it is obviously modulated by the wind direction when the wind speed is greater than 8 m/s. Furthermore, the properties of the polarization ratio, denoted PR, are also investigated. The PR is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the retrieved from new PR models as well as is in good agreement with extracted from SAR images directly.

An Investigation into the Capability of Compact Polarized SAR to Classify Multi-Sea-Surface Characteristics

ABSTRACTThis paper assesses the capability of Compact Polarized (CP) Synthetic Aperture Radar (SAR) to classify multi-sea-surface characteristics (defined as typical sea surface suspended sediments, such as oil spills algal look-alikes and algal blooms). CP reconstruction is carried out on two C-band RADARSAT-2 quad-polarized (QP) SAR images using Nord's algorithm. The accuracies of the reconstructed polarized signatures of the multi-sea-surface characteristics of open water, oil spills and algal blooms derived from QP original quad-polarized data (quad-pol) and CP reconstructed approximate quad-polarized data (namely pseudo quad-pol) are then compared and analyzed. In addition, 10 types of polarization parameters are chosen in order to investigate the accuracy of the reconstruction for open water, oil spills and algal blooms. A comparison of the results shows that, of the chosen parameters, the reconstruction accuracies for σ0HH, σ0VV, ρ, l1, l2 and α are the highest whereas the accuracies obtained for σ0HV, l3, H and A are unsatisfactory. The influence of reconstructed CP polarization parameters on the classification of multi-sea-surface characteristics is also assessed. Based on an assessment of this classification, it is concluded that the hybrid polarization (CTLR) mode should be adopted for the reconstruction of σ0HH, σ0VV, l1, H and α whereas the π/4 mode should be used for the reconstruction of σ0HV, ρ, l2 and l3.