Airborne synthetic aperture radar (SAR) data have been successfully used for forest height inversion; however, there is limited applicability in spaceborne scenarios due to high temporal decorrelation. This study investigates the potential of a high-resolution fully polarimetric interferometric pair of TerraSAR-X/TanDEM-X SAR data with no temporal decorrelation to analyze the backscatter and coherence response and to implement polarimetric SAR interferometry-based height inversion algorithms. The data were acquired over Barkot forest region of Uttarakhand state in India. Yamaguchi decomposition was implemented onto the dataset to express total backscatter as a sum of different scattering components from a single SAR resolution cell. Coherency matrix was used to compute complex coherence for different polarization channels. Forest areas suffered from low coherence due to volume decorrelation, whereas a dry river bed had shown high coherence. The coherence amplitude inversion approach overestimated the forest height and also resulted in false heights for this dry river bed. These limitations were overcome by implementing three-stage inversion modeling, which assumes polarization-independent volume coherence. The results were validated using ground truth data available for 49 plots, and the latter was found to be more accurate with an overall accuracy of 90.15% and root-mean-square error of 2.42 m.
Forest height plays a crucial role in investigating the biophysical parameters of forests and the terrestrial carbon. PolInSAR-based inversion modeling has been successfully implemented on airborne and spaceborne synthetic aperture radar (SAR) data. SAR tomography is a recent approach to separate scatterers in the cross-range direction and generate its vertical profile. This study highlights the potential of tomographic processing of multibaseline fully polarimetric Radarsat-2 C-band SAR data to estimate radar reflectivity at different forest height levels. A teak patch of Haldwani forest in Uttarakhand state of India was chosen as the test site to perform tomography. Since SAR tomography is a spectral estimation problem, Fourier transform (FT), beamforming (BF), and Capon-based spectral estimators were applied on the dataset to obtain the backscattering power contributions at different forest height levels. Fourier showed high backscatter power retrieval at different forest heights. The radar reflectivities at different heights were significantly reduced by BF followed by Capon. Tomographic profile of FT severely suffered from high sidelobes, which was drastically reduced by implementing BF. Capon further reduced the sidelobes and achieved a substantially improved tomographic profile. The height maps were generated for these algorithms and validated with ground truth data.
Forest height plays a crucial role to investigate the bio-physical parameters of forest and the terrestrial carbon. PolInSAR based inversion modeling has been successfully implemented on airborne and space-borne SAR data. SAR tomography, which is an extension of cross-track interferometric processing is a recent approach to separate scatterers in cross range direction, thus generates its vertical profile. This study highlighted the potential of tomographic processing of fully polarimetric Radarsat-2 SAR system to retrieve backscatter power at different height levels. Teak forest in Haldwani forest division of Uttarakhand state of India was chosen as the test site. Since SAR tomography is a spectral estimation problem, Fourier transform and beamforming based spectral estimations were applied on the dataset to obtain their vertical profiles. Fourier severely suffered from high side lobes which was drastically reduced by implementing beam-forming by taking into account the multi-looking effect at the expense of radiometric accuracy. Backscattered power values were found to be different at different height levels of the forest vegetation. Vertical profile for Fourier as well as beam-forming were also retrieved.
Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m-alpha and Yamaguchi decomposition modelling were extracted. The R2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha-1) and 73.424 (t ha-1) respectively. On the basis of RMSE and R2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.
Airborne SAR data has been successfully used for forest height inversion, however there is limited applicability in space borne scenario due to high temporal decorrelation. This study investigates the potential of high resolution fully polarimetric pair of TerraSAR-X/TanDEM-X SAR data acquired over Barkot forest region of Uttarakhand state in India to analyze the backscatter and coherence and to test the height inversion algorithms. Yamaguchi decomposition was implemented onto the dataset to express total backscatter as a sum of different scattering components from a single SAR resolution cell. Coherency matrix was used to compute complex coherence for different polarization channels. Forest areas suffered from low coherence due to volume decorrelation whereas dry river bed had shown high coherence. Appropriate perpendicular baseline and hence the interferometric vertical wavenumber was selected in forest height estimation. Coherence amplitude inversion (CAI) approach overestimated the forest height and also resulted in false heights for dry river bed. This limitation was overcome by implementing three stage inversion modeling (TSI) which assumes polarization independent volume coherence and the heights in dry river bed were completely eliminated. The results were validated using ground truth data available for 49 plots, and TSI was found to be more accurate with an average accuracy of 90.15% and RMSE of 2.42 m.
A new approach to reconstruction of pseudo quad-polarized data from hybrid polarimetric data has been presented in this research. The algorithm is based on certain assumptions which were validated upon testing the aptness of the results and their comparison with true optical images of the region under study. This involved direct construction of the 3X3 coherency matrix from the 2X1 scattering matrices obtained from the hybrid polarimetric data. The reasonableness of the assumptions were tested by decomposing the reconstructed pseudo quad-pol data using a coherent decomposition mechanism. The data set used in this project was Level-1 FRS-1 Hybrid Polarimetric data and FRS-2 Quad-pol data of RISAT-1. Reliable scattering retrieval from SAR data involves the calibration of the data. Polarimetric calibration was performed on real and imaginary channels of the single look complex SAR data. The newly developed algorithm was implemented on calibrated data. To extract complete information of different scattering elements of any location, second order derivative of scattering matrix is the most suitable and widely used matrix. Coherency matrix of pseudo quad-pol obtained from hybrid polarimetric data using reconstruction algorithm was decomposed using Yamaguchi four component decomposition for scattering information extraction. The obtained surface, double-bounce and volume scattering were compared with the scattering elements of hybrid-polarimetric decomposition, m-alpha and decomposition of quad-pol data of RISAT-1. The comparison revealed that the results obtained were satisfactory and thus the assumptions made during the reconstruction of pseudo quad-pol data were reasonable for specific purposes. Further comparisons of results using different decompositions technique at pixel level comparison can help better understand the aptness of the algorithm.
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