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Synthetic Aperture Radar (SAR) backscatter is the coherent combination of the scattering from multiple individual scatterers within the radar resolution cell, which results into a 2-D radar image. Tomographic SAR (TomoSAR) takes advantage of multiple SAR acquisitions to provide 3-D vertical structure of the imaged target. Over forests, parameters such as canopy structure, canopy density, leaf area and phenology contribute to different SAR scattering mechanisms along the vertical dimension of the trees. Tomography has been demonstrated in various earlier works for forest bio-physical parameter estimation using airborne data. In this research work, multi-polarimetric space-borne TanDEM-X tomograms are examined for the first time over a multi-species Indian tropical forest. Multiple TanDEM-X acquisitions are focused using Capon beamforming at five polarimetric channels — HH, HV, VV, HH − VV and HH + VV. Four distinct forest species compartments are selected representing different canopy structure and density. The tomograms obtained in different polarizations for these species are analyzed in detail to understand the scattering patterns across different forest species. Field surveys carried out in several forest locations provide in situ observations of forest height and vertical structure. It was observed that canopy gaps and leaf density play a crucial role for X-band SAR signal penetration through ground. For dense canopy species the backscatter contributions are spread through the canopy, while in case of sparse canopy species, the ground scattering is dominant. Vertical profiles obtained at surveyed plot locations are plotted in all polarizations, and provide a good agreement with field observations. Further, the obtained TomoSAR backscatter layers have a good correlation with field measured above-ground biomass (AGB). The AGB is modeled from TomoSAR with the HH-pol TomoSAR backscatter layer at 27 m canopy height leading to an AGB estimation with correlation r = 0.76 and RMSE of 50.4 t/ha. • First space-borne multi-polarimetric tomograms over Indian tropical forests • Analysis of effect of species on X-band TanDEM-X tomograms presented • SAR scattering along height of tropical forest visualized for different species • Potential of single-baseline space-borne SAR systems explored [ABSTRACT FROM AUTHOR]

3D imaging of Earth's surface layers (such as canopy, sub-surface, or ice) requires not just the penetration of radar signal into the medium, but also the ability to discriminate multiple scatterers within a slant-range and azimuth resolution cell. The latter requires having multiple radar channels distributed in across-track direction. Here, we describe the theory of multi-static radar tomography with emphasis on resolution, SNR, sidelobes, and nearest ambiguity location vs. platform distribution, observation geometry, and different multi-static modes. Signal-based 1D and 2D simulations are developed and results for various observation geometries, target distributions, acquisition modes, and radar parameters are shown and compared with the theory. Pros and cons of multi-static modes are compared and discussed. Results for various platform formations are shown, revealing that unequal spacing is useful to suppress ambiguities at the cost of increased multiplicative noise. In particular, we demonstrate that the multiple-input multiple-output (MIMO) mode, in combination with nonlinear spacing, outperforms the other modes in terms of ambiguity, sidelobe levels, and noise suppression. These findings are key to guiding the design of tomographic SAR formations for accurate surface topography and vegetation mapping. [ABSTRACT FROM AUTHOR]

Our study aims to provide a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR to assess the ability for TomoSAR to monitor and estimate the tropical forest structure parameters for enhanced forest management and to support biomass missions. The comparison relies on the unique UAVSAR Jet propulsion Laboratory (JPL)/NASA L-band data, P-band data acquired by ONERA airborne system (SETHI), Small Footprint LiDAR (SFL), and NASA Land, Vegetation and Ice Sensor (LVIS) LiDAR datasets acquired in 2015 and 2016 in the frame of the AfriSAR campaign. Prior to multi-baseline data processing, a phase residual correction methodology based on phase calibration via phase center double localization has been implemented to improve the phase measurements and compensate for the phase perturbations, and disturbances originated from uncertainties in allocating flight trajectories. First, the vertical structure was estimated from L- and P-band corrected Tomography SAR data measurements, then compared with the canopy height model from SFL data. After that, the SAR and LiDAR three-dimensional (3D) datasets are compared and discussed at a qualitative basis at the region of interest. The L- and P-band's performance for canopy penetration was assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration were compared with their ability to derive forest vertical structure. Finally, the vertical structure extracted from the 3D radar reflectivity from L- and P-band are compared with SFL data, resulting in a root mean square error of 3.02 m and 3.68 m, where the coefficient of determination shows a value of 0.95 and 0.93 for P- and L-band, respectively. The results demonstrate that TomoSAR holds promise for a scientific basis in forest management activities. [ABSTRACT FROM AUTHOR]

Developing and enhancing strategies to characterize actual forests structure is a timely challenge, particularly for tropical forests. P-band synthetic aperture radar (SAR) tomography (TomoSAR) has previously been demonstrated as a powerful tool for characterizing the 3-D vertical structure of tropical forests, and its capability and potential to retrieve tropical forest structure has been discussed and assessed. On the other hand, the abilities of L-band TomoSAR are still in the early stages of development. Here, we aim to provide a better understanding of L-band TomoSAR capabilities for retrieving the 3-D structure of tropical forests and estimating the top height in dense forests. We carried out tomographic analysis using L-band UAVSAR data from the AfriSAR campaign conducted over Gabon Lopé Park in February 2016. First, it was found that L-band TomoSAR was able to penetrate into and through the canopy down to the ground, and thus the canopy and ground layers were detected correctly. The resulting TomoSAR vertical profiles were validated with a digital terrain model and canopy height model extracted from small-footprint Lidar (SFL) data. Second, there was a strong correlation between the L-band Capon beam forming profile in HH and HV polarizations with Land Vegetation Ice Sensor (LVIS) Level 1B waveform Lidar over different kinds of forest in Gabon Lopé National Park. Finally, forest top height from the L-band data was estimated and validated with SFL data, resulting in a root mean square error of 3 m and coefficient of determination of 0.92. The results demonstrate that L-band TomoSAR is capable of characterizing 3-D structure of tropical forests. [ABSTRACT FROM AUTHOR]