Quad-pol Data Research Articles

Snow depth and snow water equivalent retrieval using X-band PolInSAR data

ABSTRACT Monitoring the dynamics of snow and glaciers in the Indian Himalaya has always attracted the attention of the remote sensing community. The snow water equivalent (SWE) represents the amount of water contained in the snowpack, and it is a product of snow depth (SD) and snow density (). The estimation of SD at high spatial and temporal resolution is still a challenge, especially in rugged mountainous terrain, like the Himalayas. In this paper, bistatic TerraSAR-X quad-polarization data is used to retrieve the SD using the Polarimetric SAR Interferometry (PolInSAR) coherences. The PolInSAR coherence at hv polarization shows a linear relationship with SD, which is verified with the field data. This relationship is utilized for the retrieval of SD using the proposed algorithm. Spatially variable is used to retrieve the SWE. The coefficient of determination () values of the retrieved SD on 8 January 2016 and 19 January 2016 are 0.62 and 0.80, respectively. Likewise, it is 0.61 and 0.72 for retrieved SWE. The root mean square error (RMSE) in SD on 8 January 2016 and 19 January 2016 are 7.00 cm and 5.48 cm, respectively; for SWE, it is 2.02 cm and 1.48 cm, respectively.

Simultaneous Single-/Dual- and Quad-Pol SAR Imaging Over Swaths of Different Widths

Synthetic aperture radar (SAR) concepts based on digital beamforming (DBF) in elevation and multiple receive beams, for example, staggered SAR, allow high-resolution imaging of wide swaths and are, therefore, well-suited for the systematic observation of dynamic processes on the Earth’s surface. While these concepts are compatible with quad-polarimetric (quad-pol) operation, due to severe ambiguity constraints, the achievable swath in the quad-pol mode is narrower than in the single- (or dual-) pol mode. Therefore, either the single- (or dual-) pol data over a wider swath or the quad-pol data over a narrower swath can be acquired. This article proposes a novel SAR acquisition mode, based on pulse-to-pulse alternation of the antenna pattern on transmit, which delivers at the same time single- (or dual-) pol data over a wider swath and quad-pol data over a narrower swath at the expense of an acceptable degradation of the ambiguity performance. This technique yields remarkable benefits for the design and operation of future SAR systems and represents an effective solution to manage and resolve conflicting user requirements.

A Small Ship Target Detection Method Based on Polarimetric SAR

The detection of small fishing ships is very important for maritime fishery supervision. However, it is difficult to detect small ships using synthetic aperture radar (SAR), due to the weak target scattering and very small number of pixels. Polarimetric synthetic aperture radar (PolSAR) has been widely used in maritime ship detection due to its abundant target scattering information. In the present paper, a new ship detector, named ΛM, is developed based on the analysis of polarization scattering differences between ship and sea, then combined with the two-parameter constant false alarm rate method (TP-CFAR) algorithm to conduct ship detection. The goals of the detector construction are to fully consider the ship’s depolarization effect, and further amplify it through sliding window processing. First, the signal-to-clutter ratio (SCR) enhancement performance of ΛM for ships with different lengths ranging from 8 to 230 m under 90 different combinations of windows are analyzed in detail using three set of RADARSAT-2 quad-polarization data, then the appropriate window size is determined. In addition, the SCR enlargement between ΛM and some typical polarization features is compared. Among these, for ships of length greater than 35 m, the average contrast of ΛM is 33.7 dB, which is 20 dB greater than that of the HV channel. For small vessels of length less than 16 m, the average contrast of ΛM is 16 dB higher than that of HV channel on average. Finally, the RADARSAT-2 data including nonmetallic small vessels are used to perform ship detection tests, and the detection ability for conventional and small ships of some classic algorithms are compared and analyzed. For large vessels of length greater than 35 m, the method proposed in this paper is able to obtain a superior detection result, maintain the ship contour well, and suppress false alarms caused by the cross side lobe in the SAR image. For small vessels of length less than 16 m, the method proposed in this paper can reduce the number of missed targets, while also obtaining superior detection results, especially for small nonmetallic vessels.

Hybrid-pol Decomposition Methods: A Comparative Evaluation and a New Entropy-based Approach

ABSTRACT The analysis of hybrid-polarimetric synthetic aperture radar (hybrid-pol SAR) data can be carried out using two different types of analytical approaches. The first approach is by implementing direct-technique (DT), which directly takes hybrid-pol Stokes parameters as input. The second approach is reconstruction-based-technique (RBT), where the pseudo quad-polarimetric (quad-pol) data is reconstructed from the hybrid-pol measurements. Methods under DT and RBT categories have their own strengths and weaknesses, which are thoroughly investigated in this paper. Also, a comparative analysis of these methods is carried out on the basis of their ability for scattering type discrimination and land-cover classification using synthesized as well as true hybrid-pol data. Moreover, a new entropy (H)-based RBT approach is proposed in this paper which is being compared with the state-of-the-art techniques.

Comparison of C- and L-band simulated compact polarized SAR in oil spill detection

This paper presents the compact polarized (CP) pseudo quad-pol parameters for the detection of marine oil spills and segregation of lookalikes using simulated CP SAR data from full-polarized (FP) SAR imagery. According to the CP theory, 11 polarized parameters generally used for the detection of oil spills were derived from reconstructed pseudo quad-pol data for both C and L bands. In addition, the reconstruction performance between C and L bands was also compared by evaluating the reconstruction accuracy of retrieved polarized parameters. The results show that apart from σHV and RH, other polarized parameters of σHH, σVV, H, α, φH–V, r, ρH–V, and γ can be reconstructed with satisfactory accuracy for both C and L bands. Furthermore, C band has a higher reconstruction accuracy than L band, especially for φH–V. Moreover, the effect of reconstruction of polarized parameters on oil spill classification was also evaluated using the maximum likelihood classification (MLC) method. According to the evaluation of kappa coefficients and mapping accuracy, it is recommended to use σHH, σVV, H, ρH–V, and γ of the C band CP SAR for marine oil spill classification.

Entropy based reconstruction technique for analysis of hybrid‐polarimetric SAR data

The analysis of hybrid-polarimetric (pol) data can be performed using any of the well-established full-pol decomposition techniques through reconstruction of pseudo quad-pol data. This reconstruction requires estimation of cross-polarisation () information from the hybrid-pol measurements. In this study, the authors established a direct relationship to estimate from hybrid-pol entropy. This proposed reconstruction approach overcomes the limitations related to the iterative based procedure implemented in the conventional Souyris’ reconstruction method. The proposed method also circumvents a non-linear co- and cross-pol linking used in Souyris’ method that holds only for volume scattering dominated areas. The comparative analysis over four different datasets indicates that the proposed method can perform better for the application of landcover classification, in comparison with conventional Souyris’ as well as recently reported Espeseth's reconstruction methods.

Retrieving Secondary Forest Aboveground Biomass from Polarimetric ALOS-2 PALSAR-2 Data in the Brazilian Amazon

Secondary forests (SF) are important carbon sinks, removing CO2 from the atmosphere through the photosynthesis process and storing photosynthates in their aboveground live biomass (AGB). This process occurring at large-scales partially counteracts C emissions from land-use change, playing, hence, an important role in the global carbon cycle. The absorption rates of carbon in these forests depend on forest physiology, controlled by environmental and climatic conditions, as well as on the past land use, which is rarely considered for retrieving AGB from remotely sensed data. In this context, the main goal of this study is to evaluate the potential of polarimetric (quad-pol) ALOS-2 PALSAR-2 data for estimating AGB in a SF area. Land-use was assessed through Landsat time-series to extract the SF age, period of active land-use (PALU), and frequency of clear cuts (FC) to randomly select the SF plots. A chronosequence of 42 SF plots ranging 3–28 years (20 ha) near the Tapajós National Forest in Pará state was surveyed to quantifying AGB growth. The quad-pol data was explored by testing two regression methods, including non-linear (NL) and multiple linear regression models (MLR). We also evaluated the influence of the past land-use in the retrieving AGB through correlation analysis. The results showed that the biophysical variables were positively correlated with the volumetric scattering, meaning that SF areas presented greater volumetric scattering contribution with increasing forest age. Mean diameter, mean tree height, basal area, species density, and AGB were significant and had the highest Pearson coefficients with the Cloude decomposition (λ3), which in turn, refers to the volumetric contribution backscattering from cross-polarization (HV) (ρ = 0.57–0.66, p-value < 0.001). On the other hand, the historical use (PALU and FC) showed the highest correlation with angular decompositions, being the Touzi target phase angle the highest correlation (Φs) (ρ = 0.37 and ρ = 0.38, respectively). The combination of multiple prediction variables with MLR improved the AGB estimation by 70% comparing to the NL model (R2 adj. = 0.51; RMSE = 38.7 Mg ha−1) bias = 2.1 ± 37.9 Mg ha−1 by incorporate the angular decompositions, related to historical use, and the contribution volumetric scattering, related to forest structure, in the model. The MLR uses six variables, whose selected polarimetric attributes were strongly related with different structural parameters such as the mean forest diameter, basal area, and the mean forest tree height, and not with the AGB as was expected. The uncertainty was estimated to be 18.6% considered all methodological steps of the MLR model. This approach helped us to better understand the relationship between parameters derived from SAR data and the forest structure and its relation to the growth of the secondary forest after deforestation events.

Capabilities of Chinese Gaofen-3 Synthetic Aperture Radar in Selected Topics for Coastal and Ocean Observations

Gaofen-3 (GF-3), the first Chinese spaceborne synthetic aperture radar (SAR) in C-band for civil applications, was launched on August 2016. Some studies have examined the use of GF-3 SAR data for ocean and coastal observations, but these studies generally focus on one particular application. As GF-3 has been in operation over two years, it is essential to evaluate its performance in ocean observation, a primary goal of the GF-3 launch. In this paper, we offer an overview demonstrating the capabilities of GF-3 SAR in ocean and coastal observations by presenting several representative cases, i.e., the monitoring of intertidal flats, offshore tidal turbulent wakes and oceanic internal waves, to highlight the GF-3’s full polarimetry, high spatial resolution and wide-swath imaging advantages. Moreover, we also present a detailed analysis of the use of GF-3 quad-polarization data for sea surface wind retrievals and wave mode data for sea surface wave retrievals. The case studies and statistical analysis suggest that GF-3 has good ocean and coastal monitoring capabilities, though further improvements are possible, particularly in radiometric calibration and stable image quality.

Performance evaluation of quad-pol data compare to dual-pol SAR data for river ice classification

ABSTRACT Satellite SAR data are a unique source of information about river ice since the microwaves penetrate through clouds as well as snow and ice cover. The influence of the number of polarization channels on the nature and amount of information is, however, not yet fully investigated. The article intends to compare quad-pol and dual-pol data. The studied areas include two rivers with different types of ice cover – the Peace River in Canada and the Vistula River in Poland. We used RADARSAT-2 quad-pol Single Look Complex (SLC) data. The comparison methods include separability analysis (Hellinger distance, Bhattacharyya distance) and Wishart supervised classification. We found that dual-pol and quad-pol data provide equivalent information for homogeneous ice cover (overall classification accuracy above 80% for all polarization modes). Differences were observed in case of complex river ice cover with high diversity of ice types.

Estimating canola phenology using synthetic aperture radar

Prolonged periods of wet soil conditions, when present during critical crop development stages, can significantly elevate the risk of some crop diseases. Wet soils in fields of flowering canola are a concern with respect to the development of sclerotinia as this pathogen feeds on the petals of the canola flower. As such, determining if canola is in bloom during periods of high moisture is important in deciding whether to take action to mitigate this disease. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization Synthetic Aperture Radar (SAR) data were used with a novel dynamic filtering framework to estimate canola growth stages. In this process, a new crop growth stage indicator was developed and SAR polarimetric parameters sensitive to changes in phenology were identified. Model development used multi-year SAR satellite and field data for one site in Manitoba, Canada. The crop growth estimator was then tested on unseen data from three sites, one in each of Canada's Prairie provinces. This independent validation established that the growth estimator was able to accurately determine canola growth stage and date of flowering with high accuracy. Correlation coefficients (r-values) between observed and estimated phenology ranged from 0.91 to 0.96. Given that this method performed well on test data from other sites and years, this approach could be widely adopted for monitoring the development of canola over extended regions.

Insights Into Polarimetric Processing for Wetlands From Backscatter Modeling and Multi-Incidence Radarsat-2 Data

We have observed unexpected results using the Freeman–Durden (FD) and other polarimetric decompositions in Radarsat-2 quad-pol data from many swamps in Eastern Ontario. In particular, the decompositions reported minimal backscatter from the double-bounce mechanism in a situation where there was compelling evidence that double-bounce backscatter contributed substantially to the return. This led to a hypothesis that the FD and similar models give erroneous results because of the physics of Fresnel reflection of wood, a lossy dielectric material, that makes up the vertical reflecting surfaces in swamps. We found some support for this hypothesis in the literature, and now report on an extensive theoretical and observational investigation. This work has shown that the Freeman-Durden decomposition, and other decompositions that use the same logic, will often mistake double-bounce backscatter as single-bounce backscatter in wetlands. This is a consequence of the fundamental physics of Fresnel reflection. It is important for users to be aware of this pitfall. Double-bounce backscatter from natural surfaces can be identified without recourse to polarimetric decomposition. The simplest, and most reliable, indicator of double-bounce backscatter is a high return in HH polarization. Double-bounce backscatter will generally produce higher return in HH than any other scattering mechanism. If both HH and VV polarizations are available, a high HH/VV intensity ratio is also a strong indicator of double-bounce backscatter. Additional modeling efforts are expected to provide further insights that can lead to improved applications of polarimetric data.

Ocean Wave Information Retrieval Using Simulated Compact Polarized SAR from Radarsat-2

The main objective of this paper is to demonstrate the capability of compact polarized (CP) synthetic aperture radar (SAR) to retrieve ocean wave field parameters. Souyris’ and Nord’s algorithms are used to carry out the reconstruction of CP SAR pseudo quad-polarized data for the ocean surface under both the circular transmit linear receive (CTLR) and π/4 mode. The results show that, for the CP reconstruction, Nord’s algorithm has a better convergence ability than Souyris’. In addition, the investigation of the reconstruction accuracy shows that the CTLR mode is superior to the π/4 mode, in terms of ocean surface reconstruction. It is, therefore, concluded that the reconstructed parameters of CP CTLR mode data by Nord’s algorithm adapt to retrieve ocean wave information. The ocean wave slope spectrum and other main wave parameters are also calculated from reconstructed CP data and compared with measurements from in situ National Data Buoy Center (NDBC) matched-up buoys. Comparison of CP SAR-based wave field information with buoy outputs also shows good agreement in the case of dominate wave height, wave direction, and wave period, with biases of 0.36 m, 17.96°, and 0.88 s, respectively.

Effect of wind direction and incidence angle on polarimetric SAR observations of slicked and unslicked sea surfaces

The objective of this paper is to investigate the dependency of oil spill observations in polarimetric SAR data on imaging geometry, i.e., on incidence angle and look direction relative to the wind. The study is based on quad-polarization data acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar over experimental oil slicks under relatively high winds of 10–12 m/s over an 8-hour period. The data is collected over a wide range of incidence angles and alternates between looking upwind (UW) and downwind (DW). The unique time series enables a detailed study of the behavior of multipolarization parameters over clean sea and oil slicks under varying imaging geometry to be carried out for the first time. For clean sea backscatter, our findings are in agreement with previous studies, showing decreasing backscatter as the incidence angle increases and from UW to DW, with the highest sensitivity in the HH channel. We also find similar variations in oil covered areas. The results suggest that the oil slick backscatter is slightly more sensitive to the relative wind direction than the clean sea, and higher oil-sea damping ratios are found in DW than in UW cases, particularly in the HH channel. All multipolarization features investigated have some degree of dependency on imaging geometry. The lowest sensitivities are found in the magnitude of the copolarization correlation coefficient, the standard deviation of the copolarized phase difference, the polarization difference, the mean scattering angle and the entropy. Several features clearly change behavior when the signal approaches the sensor noise floor, and we find that the measurements and derived parameters may be affected at even higher signal-to-noise ratio (SNR) levels than previously proposed, i.e., closer to 7–9 dB above the sensor noise floor. Overall, the polarization difference is clearly identified as the most interesting parameter for oil spill observation, producing high oil-sea contrast in addition to low sensitivity to imaging geometry. The results show that both the relative wind direction and the incidence angle, in combination with the SNR, should be taken into account when developing operational methods based on multipolarization SAR data.

A NOVEL TWO-COMPONENT DECOMPOSITION FOR CO-POLAR CHANNELS OF GF-3 QUAD-POL DATA

Abstract. Polarimetric target decomposition theory is the most dynamic and exploratory research area in the field of PolSAR. But most methods of target decomposition are based on fully polarized data (quad pol) and seldom utilize dual-polar data for target decomposition. Given this, we proposed a novel two-component decomposition method for co-polar channels of GF-3 quad-pol data. This method decomposes the data into two scattering contributions: surface, double bounce in dual co-polar channels. To save this underdetermined problem, a criterion for determining the model is proposed. The criterion can be named as second-order averaged scattering angle, which originates from the H/α decomposition. and we also put forward an alternative parameter of it. To validate the effectiveness of proposed decomposition, Liaodong Bay is selected as research area. The area is located in northeastern China, where it grows various wetland resources and appears sea ice phenomenon in winter. and we use the GF-3 quad-pol data as study data, which which is China’s first C-band polarimetric synthetic aperture radar (PolSAR) satellite. The dependencies between the features of proposed algorithm and comparison decompositions (Pauli decomposition, An&Yang decomposition, Yamaguchi S4R decomposition) were investigated in the study. Though several aspects of the experimental discussion, we can draw the conclusion: the proposed algorithm may be suitable for special scenes with low vegetation coverage or low vegetation in the non-growing season; proposed decomposition features only using co-polar data are highly correlated with the corresponding comparison decomposition features under quad-polarization data. Moreover, it would be become input of the subsequent classification or parameter inversion.

DETECTION OF LANDSLIDES WITH SAR POLARYMETRY: CASE STUDY OF SOUTH-EASTERN COLOMBIA

Abstract. SAR polarimetry (PolSAR) is a method that can be used to investigate landslides. Polarimetric scattering power decomposition allows to separate the total power received by the SAR antenna, which is divided in surface scattering power, double bounce scattering and volume scattering power. Polarimetric indices are expected to serve for landslide recognition, because landslides’ scattering properties are different from those of the surrounding forested areas. The surface scattering mechanism is mainly caused by rough surfaces like bare soil and agricultural fields, so we hope that this will be the predominant dispersion mechanism in landslides. In a study area located in south-western Colombia, we used dual-Pol provided by ESA’s Sentinel-1 satellites and quad-pol from NASA’s UAVSAR aerial platform. Using C-band and L-band radar images, we analysed the interaction between radar signals and landslides. First, with dual-pol we found backscatter calibrate coefficients over four GRD radar images acquired between 2015 and 2017. The analysis gave an average backscatter value of −14.47 dB for VH polarisation and −8.40 dB for VV polarisation. Then, using H-a decomposition for quad-pol data, we validated the high relationship between entropy and alpha parameter, which has the highest contribution to the first axis in a principal component analysis. These results were used to obtain an unsupervised classification of landslides, that separated the Colombian Geological Service landslide inventory in three classes characterized by the mechanism of dispersion. These results will be combined with InSAR parameters, morphometric parameters and optical spectral indexes to obtain a local detection model of landslides.

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.

Performance Evaluation of TanDEM-X Quad-Polarization Products in Bistatic Mode

In the TanDEM-X mission, quad-polarization data (HH, HV, VH, and VV-polarization channels) can be acquired at an experimental basis by acquiring images in the dual-receive antenna (DRA) mode. This mode was activated during the so-called TanDEM-X science phase, from October 2014 up to January 2016, serving the science community with a unique dataset for the demonstration of new SAR techniques and applications. Quad-polarization data has been firstly acquired in pursuit monostatic mode and, secondly, in bistatic configuration as well. TanDEM-X is the first spaceborne mission which allows for the acquisition of quad-polarization data in bistatic formation, with across-track baselines varying up to 4 km at the Equator. The current work completes the one presented in [1] , where TanDEM-X quadpolarization data, acquired in pursuit monostatic mode only, was analyzed and recommendations were drawn, in order to optimize the acquisition parameters, aiming at improving the final data quality. Such recommendations were then taken into account for the acquisition of quad-polarization data in bistatic configuration, starting from April 2015, and the obtained results are presented in this paper. Investigations have been performed, aiming at monitoring the effective improvement in data quality. For example, we investigated the impact of different system parameters, such as noise equivalent sigma zero (NESZ) or processing bandwidth on the SAR performance, together with their influence on the interferometric SAR (InSAR) performance, assessed in terms of interferometric coherence and relative height error. Finally, we introduce and discuss an experimental acquisition mode, which allows to synthesize a quad-polarization product by combining two simultaneous dual-polarization acquisitions.

A Review on Recent Developments in Fully Polarimetric SAR Image Despeckling

The use of synthetic aperture radar (SAR) technology with quad-polarization data requires efficient polarimetric SAR (PolSAR) speckle filtering algorithms. During the last three decades, many effective methods have been developed to reduce the speckle in PolSAR images, and recent studies have generally shown a trend developing from local single-point filtering to nonlocal patch-based or globally collaborative filtering. The main goals of this paper are to make a comprehensive review of the existing PolSAR despeckling algorithms and highlight the recent development trends. In the experimental part, the filtering results obtained with both simulated and real PolSAR images are deployed to compare the performance of some of the state-of-the-art despeckling algorithms, which shows that all of the selected filters have their individual strengths and weaknesses.

Wetland classification using Radarsat-2 SAR quad-polarization and Landsat-8 OLI spectral response data: a case study in the Hudson Bay Lowlands Ecoregion

ABSTRACTCircumboreal Canadian bogs and fens distinguished by differences in soils, hydrology, vegetation and morphological features were classified using combinations of Radarsat-2 synthetic aperture radar (SAR) quad-polarization data and Landsat-8 Operational Land Imager (OLI) spectral response patterns. Separate classifications were conducted using a traditional pixel-based maximum likelihood classifer and a machine learning algorithm following an object-based image analysis (OBIA). This study focused on two wetland classes with extensive coverage in the area (bog and fen). In the pixel-based maximum likelihood classification, accuracy increased from approximately 69% user’s accuracy and 79% producer’s accuracy using Radarsat-2 SAR data alone to approximately 80% user’s accuracy and 87% producer’s accuracy using Landsat-8 OLI data alone. Use of the Radarsat-2 SAR and Landsat-8 OLI data following principal components analysis (PCA) data fusion did not result in higher pixel-based maximum likelihood classification accuracy. In the object-based machine learning classification, higher bog and fen class accuracies were obtained when using Radarsat-2 and Landsat OLI data individually compared to the equivalent pixel-based classification. Subsequently, a PCA-data fusion product outperformed the individual bands of the Radarsat-2 and Landsat-8 imagery in object-based classification. Greater than 90% producer’s accuracy was obtained. The margin of error (MOE) was less than 5% in all classifications reported here. Further research will examine alternative data fusion techniques and the addition of Radarsat-2 SAR interferometric digital elevation model (DEM)-based geomorphometrics in object-based classification of different morphological types of bogs and fens.

Preliminary Analysis of Chinese GF-3 SAR Quad-Polarization Measurements to Extract Winds in Each Polarization

This study analyzed the noise equivalent sigma zero (NESZ) and ocean wind sensitivity for Chinese C-band Gaofen-3 (GF-3) quad-polarization synthetic aperture radar (SAR) measurements to facilitate further operational wind extraction from GF-3 data. Data from the GF-3 quad-polarization SAR and collocated winds from both NOAA/NCEP Global Forecast System (GFS) atmospheric model and National Data Buoy Center (NDBC) buoys were used in the analysis. For NESZ, the co-polarization was slightly higher compared to the cross-polarization. Regarding co-polarization and cross-polarization, NESZ was close to RadarSAT-2 and Sentinel-1 A. Wind sensitivity was analyzed by evaluating the dependence on winds in terms of normalized radar cross-sections (NRCS) and polarization combinations. The closest geophysical model function (GMF) and the polarization ratio (PR) model to GF-3 data were determined by comparing data and the model results. The dependence of co-polarized NRCS on wind speed and azimuth angle was consistent with the proposed GMF models. The combination of CMOD5 and CMOD5.N was considered to be the closest GMF in co-polarization. The cross-polarized NRCS exhibited a strong linear relationship with moderate wind speeds higher than 4 m·s−1, but a weak correlation with the azimuth angle. The proposed model was considered as the closest GMF in cross-polarization. For polarization combinations, PR and polarization difference (PD) were considered. PR increased only with the incidence angle, whereas PD increased with wind speed and varied with azimuth angle. There were three very close PR models and each can be considered as the closest. Preliminary results indicate that GF-3 quad-polarization data are valid and have the ability to extract winds in each polarization.