Polarization Orientation Angle Shift Research Articles

A Computationally Efficient Hybrid Framework for Polarimetric Calibration of Quad‐Pol SAR Data

AbstractPolarimetric Synthetic Aperture Radar (PolSAR) calibration is an essential preprocessing step that must be performed to ensure that the data quality is adequate. This, in turn, helps to minimize the propagation of errors in any further data processing or information extraction. Crosstalk and channel imbalance are two major distortions found to be present in the uncalibrated polarimetric SAR data. The PolSAR calibration mainly aims to reduce these two distortions revealing the true scattering pattern of the targets. In this regard, Quegan's algorithm and Ainsworth algorithm are two widely used algorithms for the PolSAR calibration. In this study, the accuracy and efficiency of these two algorithms have been thoroughly compared using suitable metrics. It has been shown that the Ainsworth algorithm performs better than Quegan's in terms of accuracy at the cost of poor computational efficiency. The data quality metrics also highlight the better calibration accuracy of the Ainsworth algorithm. The issue of higher computational complexity has been effectively addressed by coupling both of these algorithms. Evidently, the computational cost has been reduced in the case of the proposed algorithm. The polarization orientation angle (POA) shift is another distortion caused by the topographic variations present in the target scene. Therefore, correction of POA shift has been incorporated in this research by coupling it with the PolSAR calibration. Subsequently, the improvement in the scattering has been observed. In essence, the proposed algorithm coupled with the correction of POA shift rectifies the major polarimetric distortions with adequate accuracy and computational efficiency.

Investigation on the Effects of Polarization Orientation Angle Shift in the UAVSAR Polarimetric Decomposition

The polarization orientation angle (POA) shift results in higher cross-polarization intensity in the HV and VH channels making the reflection asymmetrical. The L-band quad-pol dataset acquired over the Fujiyama mountain, Japan by the Uninhabited Aerial Vehicle Synthetic Aperture Radar of JPL/NASA was used in this study to analyse the effect of POA shift in the polarimetric decomposition techniques. The dataset was first compensated for the POA shift using the circular polarization algorithm, and a mean polarization orientation angle shift of − 4.23° was estimated. The Yamaguchi 3-component model-based decomposition and the H/A/Alpha eigenvector-based decomposition techniques were performed on the dataset before and after POA compensation. It was found that there was an overestimation of volume scattering component and underestimation of double-bounce scattering component before POA compensation in the Yamaguchi 3-component decomposition technique. After the POA compensation, there was a significant reduction in the volume scattering component observed at the non-vegetated areas and increase in double-bounce scattering in the same areas. There was no considerable change observed in the surface scattering component because of its roll invariant nature. Since the H/A/Alpha decomposition parameters were also independent of the orientation angle change because of their roll invariance property, there was no change observed in those parameters after POA compensation.

PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation

Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR resolution cell. A methodology for a PolSAR-based extended water cloud model (EWCM) has been proposed and evaluated in this study. Fully polarimetric phased array type L-band synthetic aperture radar (PALSAR) data of advanced land observing satellite (ALOS) was used in this study for forest aboveground biomass (AGB) retrieval of Dudhwa National Park, India. The shift in the polarization orientation angle (POA) is a major problem that affects the PolSAR-based scattering information. The two sources of POA shift are Faraday rotation angle (FRA) and structural properties of the scatterer. Analysis was carried out to explore the effect of FRA in the SAR data. Deorientation of PolSAR data was implemented to minimize any ambiguity in the scattering retrieval of model-based decomposition. After POA compensation of the coherency matrix, a decrease in the power of volume scattering elements was observed for the forest patches. This study proposed a framework to extend the water cloud model for AGB retrieval. The proposed PolSAR-based EWCM showed less dependency on field data for model parameters retrieval. The PolSAR-based scattering was used as input model parameters to derive AGB for the forest area. Regression between PolSAR-decomposition-based volume scattering and AGB was performed. Without deorientation of the PolSAR coherency matrix, EWCM showed a modeled AGB of 92.90 t ha−1, and a 0.36 R2 was recorded through linear regression between the field-measured AGB and the modeled output. After deorientation of the PolSAR data, an increased R2 (0.78) with lower RMSE (59.77 t ha−1) was obtained from EWCM. The study proves the potential of a PolSAR-based semiempirical model for forest AGB retrieval. This study strongly recommends the POA compensation of the coherency matrix for PolSAR-scattering-based semiempirical modeling for forest AGB retrieval.

POLINSAR BASED SCATTERING INFORMATION RETRIEVAL FOR FOREST ABOVEGROUND BIOMASS ESTIMATION

Abstract. Forests play a crucial role in storing carbon and are of paramount importance in maintaining global carbon cycle. Assessment of forest biomass at regional and global level is vital for understanding and monitoring health of both tree species and entire cover. Changes in forest biomass are caused by human activities, natural factors and variations in climate. Forest biomass measurement is necessary for gauging the changes in forest ecosystems. Remote sensing is indispensable for mapping forest biophysical parameters. Microwaves are capable of collecting data even in case of cloud cover as the microwaves are of long wavelength. Microwaves help in retrieving scattering information of target. The goal of this research was to map aboveground biomass (AGB) over Barkot forest range in Dehradun, India. The current work focuses on the retrieval of PolInSAR based scattering information for the estimation of aboveground biomass. Radarsat-2 fully Polarimetric C-band data was used for the estimation of AGB in Barkot forest area. A semi-empirical model, which is Extended Water Cloud Model (EWCM) was utilized for AGB estimation. EWCM considers ground-stem interactions. Due to overestimation of volume scattering, polarization orientation angle shift correction was implemented on the PolInSAR pair. Field biomass data was utilized for accuracy assessment. The results show that coefficient of determination (R2) value of 0.47, Root Mean Square Error (RMSE) of 56.18 (t ha−1) and accuracy of 72% was obtained between modelled biomass against field measured biomass. Hence, it can be inferred from the obtained results that PolInSAR technique, in combination with semi-empirical modelling approach, can be implemented for estimating forest biomass.

SRTM DEM enhancement using a single set of PolSAR data based on the polarimetry-clinometry model

ABSTRACT The freely available global and near-global digital elevation models (DEMs) have shown great potential for various remote sensing applications. The Shuttle Radar Topography Mission (SRTM) data sets provide the near-global DEM of the Earth’s surface obtained using the interferometry synthetic aperture radar (InSAR). Although free accessibility and generality are the advantages of these data sets, many applications require more detailed and accurate DEMs. In this paper, we proposed a modified and advanced polarimetry-clinometry algorithm for improving SRTM topography model which requires only one set of polarimetric synthetic aperture radar (PolSAR) data. The azimuth and range slope components estimation based on polarization orientation angle (POA) shifts and the intensity-based Lambertian model formed the bases of the proposed method. This method initially compensated for the polarimetry topography effect corresponding to SRTM using the DEM-derived POA. In the second step, using a modified algorithm, POA was obtained from the compensated PolSAR data. The POA shifts by the azimuth and range slopes’ variations based on the polarimetric model. In addition to the polarimetric model, a clinometry model based on the Lambertian scattering model related to the terrain slope was employed. Next, two unknown parameters, i.e. azimuth and range slope values, were estimated in a system of equations by two models from the compensated PolSAR data. Azimuth and range slopes of SRTM were enhanced by PolSAR-derived slopes. Finally, a weighted least-square grid adjustment (WLSG) method was proposed to integrate the enhanced slopes’ map and estimate enhanced heights. The National Aeronautics and Space Administration Jet Propulsion Laboratory (NASA JPL) AIRSAR was utilized to illustrate the potential of the proposed method in SRTM enhancement. Also, the InSAR DEM was employed for evaluation experiments. Results showed that the accuracy of SRTM DEM is improved up to 2.91 m in comparison with InSAR DEM.

Analysis of Orientation Angle Shifts on the Polarimetric Data Using Radarsat2 Images

Polarization orientation angle (POA) shifts induced by the variations of range and azimuth slopes cause the polarization to rotate about the radar line of sight. Their existence reduces the accuracy measurement of geophysical parameters from polarimetric synthetic aperture radar (PolSAR) images and may generate erroneous scattering characteristics that could be misinterpreted. In real situations, terrain slopes rotate the polarization basis of the polarimetric scattering matrices by an orientation angle shift, and induce significant cross-polarization power. Consequently, it is desirable to compensate the data for the orientation effect before applying scattering model-based decompositions. In this paper, we investigate the compensation effect on the elements of the coherency matrix using the orientation angle extracted from circular polarization technique and from the copolarization signature applied to building areas. The effect of this compensation is that the volume scattering power is consistently decreased, while the double-bounce power is increased. The surface and helix scattering powers are roll invariant. Comparing both methods, we find that the circular polarization algorithm gives mostly the best results except for some targets. In this way, a combined use of both algorithms has been proposed to choose an optimum orientation angle, which can be used directly to compensate POLSAR data to ensure improvement in the overall polarimetric decomposition and classification. We illustrate our results using the polarimetric SAR images acquired on the Algiers city by the RadarSAT2 (FQ19) in C-band.

Polarimetric Calibration of CASMSAR P-Band Data Affected by Terrain Slopes Using a Dual-Band Data Fusion Technique

For airborne synthetic aperture radar (SAR) polarimetric calibration (PolCAL) based on distributed targets, it is important to ensure the removal of both the polarimetric distortion and terrain slope effect. This paper proposes a new technique for PolCAL in mountainous areas, without the use of corner reflectors (CRs). The technique based on dual-band data fusion consists of two steps. First, the polarization orientation angle shift (POAS), as a priori asymmetry information, is derived from X-band interferometry and applied to P-band fully-polarimetric data. Second, the crosstalk and cross-polarization (cross-pol) channel imbalance are iteratively determined using the POAS after dual-band data fusion. The performance and feasibility of the technique was evaluated by CRs. It was demonstrated that the proposed technique is capable of deriving the distortion parameters and performs better than the methods presented in Quegan and Ainsworth et al. The signal-to-noise ratio (SNR) and pedestal height have been investigated in polarimetric signatures. The proposed technique is useful for PolCAL in mountainous areas and for monitoring systems without CRs in long-term operation.

Automatic GCP Extraction in Mountainous Areas Using DEM and PolSAR Data

Mountainous areas in synthetic aperture radar (SAR) images suffer severe geometric distortions caused by different look directions. Consequently, ground control point (GCP) extraction hardly obtains accurate results for aircraft positioning. Based on the digital elevation model (DEM) and polarimetric SAR (PolSAR) data, we propose a method for extracting GCPs in mountainous areas by introducing the polarization orientation angle shift (POAS) to minimize geometric distortions. In this method, DEM data are used as the reference map by providing POASs at arbitrary look directions to make up for the look-direction sensitivity of POASs transformed from PolSAR data. The geometric distortions between POASs transformed from DEM and PolSAR data are effectively reduced by calculating the POASs from DEM data at the same look direction and look angles of the PolSAR data. In contrast to the SAR data, which have a large dynamic range, the values of POAS are limited to a small interval. Therefore, the illumination distortions induced by visualization can be reduced. Finally, the GCP extraction between the POAS images is conducted by bilateral filter scale-invariant feature transform. Experiments using various data at different look directions demonstrate that the proposed method obtains better-quality GCPs but less invalid keypoints than the method using only intensity images for mountainous areas.

AN IMPROVED SAR RADIOMETRIC TERRAIN CORRECTION METHOD AND ITS APPLICATION IN POLARIMETRIC SAR TERRAIN EFFECT REDUCTION

A new SAR radiometric terrain correction method was proposed to reduce the terrain efiects in sloped regions. Based on this method, a procedure for polarimetric SAR terrain efiect reduction was proposed, including geometric correction, shadow detection, radiometric terrain correction, and polarization orientation angle shift compensation. Experiments using RADARSAT-2 polarimetric SAR data of the Three Gorges Area, China demonstrated the efiectiveness of the proposed radiometric terrain correction method. Both visual and quantitative analyses showed that after the proposed radiometric terrain correction method was applied, the contrast between difierent slopes that caused by local incidence angle difierences, foreshortening, and layover was signiflcantly reduced. The difierence of backscattering intensity on slopes facing the radar sensor and facing away from the sensor was reduced from 12.5dB before radiometric correction to 1.3dB. The overall accuracy of land use/land cover classiflcation was improved by 11.2 percent using the terrain corrected polarimetric SAR data.

DEM Generation Combining SAR Polarimetry and Shape-From-Shading Techniques

Estimation of the polarization orientation angle shifts induced by terrain azimuth slope variations is a recently developed application in radar polarimetry. In general, without any prior knowledge on the terrain, two polarimetric SAR (POLSAR) flight passes are required to derive terrain slopes in perpendicular directions for digital elevation model (DEM) generation. Moreover, we note that SAR intensity is a strong indicator of the range component of the terrain slopes. In this letter, we developed a method for DEM generation requiring only one POLSAR flight pass, by combining orientation angle estimation and a shape-from-shading technique. In particular, when limited POLSAR data are available, this POLSAR technique provides an alternative way for DEM generation. National Aeronautics and Space Administration Jet Propulsion Laboratory (NASA/JPL) AIRSAR L-band POLSAR data over Camp Roberts, California, is used to demonstrate the results of the method proposed in this letter, and a DEM derived from simultaneously measured C-band interferometric SAR from NASA/JPL topographic SAR instrument is selected as the comparative ground truth to validate the effectiveness of this single POLSAR method. Analyses and discussions are also included in this letter.

Radar Polarization Orientation Shifts in Built-Up Areas

Polarization orientation angle shifts can be seen not only in rugged terrain areas but also in urban areas. The latter is explained by backscatter from a wall of a building or house, which is equivalent to a tilted ground-surface patch. From the scattering model of built-up areas, the polarization orientation angle shift in the built-up areas is given as , where is the wall or street orientation angle, and is the radar incidence angle. Japan Aerospace Exploration Agency Pi-SAR L-band polarimetric data of Gifu, Japan, show a good agreement with the theory. The phase difference between VH and HH polarizations is used to demonstrate the contribution of double-bounce scattering ground-wall and wall-ground over a wide range of wall orientation angles.

Analysis of Polarization Orientation Angle Shifts by Artificial Structures

In this paper, the polarization orientation angle shifts induced by artificial structures were analyzed and attempted to combine target orientation information which characterizes an urban area with the polarization orientation angle information extracted by the circular-polarization method. In order to illustrate the characteristic of the polarization orientation angle shifts represented in an urban area, the X-band polarimetric synthetic aperture radar (SAR) datasets of Sendai City acquired by Pi-SAR were used. This paper is based on Kimura's idea that the variation of the polarization orientation angle shifts depends on the artificial structures, particularly for the target rotation angle. We found that the polarization orientation angle shift is also affected by the relative relationship between the target rotation angle and the flight direction. From these results, it is possible to estimate the target rotation angle via computation of the polarization orientation angle shift from polarimetric SAR data.