Conference Agenda

Forest parameters inversion is essential for quantifying carbon cycle dynamics, monitoring climate change, and sustaining global ecological balance. Recently, long-wavelength Synthetic Aperture Radar (SAR) Tomography (TomoSAR) has gained increasing interest for forest parameter inversion due to its excellent three-dimensional (3D) imaging and penetration capabilities. This paper presents an airborne TomoSAR processing framework, starting from raw radar echo data, proceeding to focused SAR image stacks, followed by 3D tomographic reconstruction, and finally forest parameter inversion. Compared with other SAR imaging algorithms, the Time Domain Back Projection (TDBP) algorithm does not rely on the straight flight path assumption and therefore does not require additional motion compensation operations, leading to higher robustness. To improve its computational efficiency, the algorithm is first accelerated using GPU parallel processing. Furthermore, the two-dimensional antenna pattern and range attenuation effects of the radar signal are taken into account by utilizing high-precision airborne trajectory and attitude data to ensure the radiometric accuracy of the SAR images. Even with high-precision navigation data, residual centimeter-level trajectory errors can lead to non-negligible misregistration and phase errors among SAR image stacks, which in turn degrade the quality of 3D imaging. A two-stage airborne trajectory error correction algorithm is developed for compensating multi-baseline trajectory errors to ensure high-quality TomoSAR imaging. The first stage corrects the trajectory errors of each baseline using strong scatterer echoes based on the Phase Gradient Autofocus (PGA) concept, while the second stage further refines the relative trajectory errors among baselines by exploiting interferometric information from distributed scatterers following the Multisquint approach.

The method is applied to an area of approximately 200 km² in the Saihanba Mechanical Forest Farm, the largest man-made forest and a national forest park in China. Located in the temperate zone of northern China, this forest is dominated by Pinus sylvestris, Larix gmelinii, Betula platyphylla, and Picea asperata. An airborne P-band TomoSAR campaign was conducted over the study area in October, 2023. Twelve tracks of P-band quad-polarization SAR data were acquired, providing azimuth, range, and height resolutions of 0.9 m, 0.75 m, and 5 m, respectively. Based on the TomoSAR results of HH and HV polarizations, the underlying topography and forest height of the Saihanba Forest were retrieved, showing good consistency with a 10 m-resolution airborne LiDAR topography product and a 1 m-resolution forest height product from Meta and the World Resources Institute.

We have been approved to carry out the Biomass Cal/Val project (ID: PP0106173), and plan to perform spaceborne TomoSAR imaging and forest parameter retrieval based on the Biomass Level-1C data acquired over the Saihanba Forest during the Commissioning phase of the Biomass satellite. Based on the previous airborne P-band TomoSAR forest parameters retrieval results, the accuracy of spaceborne P-band TomoSAR forest parameters retrieval will be evaluated, and the effects of temporal decorrelation on spaceborne TomoSAR will be analyzed.