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Polarimetric synthetic‐aperture radar (SAR) remote sensing has been widely used for structural and biophysical parameters retrieval of forest vegetation. It has been found that the combination of polarimetric properties and interferometric characteristics of SAR remote sensing provides the capacity to retrieve forest height. The prime objective of this research was to investigate the potential of Polarimetric Synthetic Aperture Radar Tomography (PolTomSAR) for the forested and river region of Mondah National Park, Gabon. SAR tomography is an improved method for acquiring the height of geographical features. UAVSAR L‐band fully polarimetric multibaseline data have been used in this research (1.275 GHz). SAR data and ground data over the area have been collected in the year 2016. With the superresolution‐based Capon algorithm, multiple scatterers located at a different vertical position in the same azimuth range cell has been resolved and reconstructed. This work provides a framework for Capon‐based tomographic processing of multibaseline UAVSAR data for vertical profile retrieval of forest vegetation. The height profile of the forest patch having sparse, as well as dense vegetation, were retrieved. The vertical profile for a single azimuthal bin was obtained in range direction. The tomographic profile obtained was cross‐checked with the field‐measured forest height for the 16 locations in Mondah National Park, Gabon. To check the accuracy of the applied method, the statistical method of R2 and root‐mean‐square error (RMSE) is employed. The obtained RMSE of the result is 4.21 m and R2 is 0.92. The obtained results were concluded to find the potential of the Capon algorithm for the tomographic reconstruction of UAVSAR data. Key Points: PolSAR Tomography of UAVSAR data for forest height retrievalAn analysis of tomographic profiles for forest vegetation and water bodyAccuracy assessment of PolSAR tomography‐based forest height retrieval [ABSTRACT FROM AUTHOR]

The Polarimetric Synthetic Aperture Radar (PolSAR) systems use electromagnetic radiations of different polarizations in the microwave frequency to collect the scattering information from targets on the Earth. Nevertheless, as with any other electronic device, the PolSAR systems are also not ideal and subjected to distortions. The most important of these distortions are the polarimetric distortions caused due to the channel imbalance, phase bias, and crosstalk between the different polarization channels. For the spaceborne PolSAR systems, the Earth's ionosphere also contributes to an additional polarimetric distortion known as the Faraday rotation. An effort was made in this study to perform the polarimetric calibration of the Quad-pol and Compact-pol PolSAR datasets acquired using different airborne and spaceborne PolSAR systems to estimate and minimize these polarimetric distortions. The investigation was also done to analyze the impact of these polarimetric distortions on the scattering mechanisms from ground targets and on its dependency on the radar wavelength. The study was done using the UAVSAR L-band Quad-pol dataset, RADARSAT-2 Quad-pol dataset, ALOS-2 PALSAR-2, ISRO's L&S- Band Airborne SAR (LS-ASAR) Quad-pol and Compact-pol datasets, and the RISAT-1 Compact-pol dataset. Calibration of the airborne PolSAR data was carried to understand the level of polarimetric distortions in the LS-ASAR product that is a precursor mission to the spaceborne Dual-Frequency L&S Band NASA-ISRO Synthetic Aperture Radar (NISAR) mission. It is understood that the crosstalk is the dominant polarimetric distortion, which severely affects the PolSAR datasets compared to the other polarimetric distortions, and it is more for the higher wavelength PolSAR systems. The Quegan, Improved Quegan, and Ainsworth algorithms for crosstalk estimation and minimization was performed for the different Quad-pol datasets and it was found that the Improved Quegan algorithm is suitable for removing crosstalk from datasets having high crosstalk and the Ainsworth algorithm is suitable for removing crosstalk from datasets having low crosstalk. The Freeman method of the polarimetric calibration was implemented for the compact-pol datasets and it was able to considerably minimize the polarimetric distortions. The coherency matrix, scattering matrix, model-based decomposition, polarimetric signatures, and roll invariant parameter-based analysis revealed that all the datasets after polarimetric calibration were showing the correct scattering responses expected from the ground targets. [ABSTRACT FROM AUTHOR]