A Multibaseline Forest Height Inversion Method to Solve Three General Problems in P-Band Repeat-Pass PolInSAR Data

P-band polarimetric interferometric synthetic aperture radar (PolInSAR) has the potential to map forest height and biomass at the global scale with the upcoming BIOMASS mission. However, because of the strong penetration of P-band and temporal decorrelation of repeat-pass observations, volume temporal decorrelation (VTD) (?(VT)), ground temporal decorrelation (?(GT)), and residual ground scattering (m(min)) largely influence forest height inversion. By integrating the random volume over ground (RVoG) model and sum of Kronecker products (SKP) decomposition, this study proposed a multibaseline forest height inversion method to remove the joint influence of these problems. The theoretical simulation and empirical experiments using airborne P-band PolInSAR data in tropical forests, Nouragues, explicitly explored how each of the three problems affects the inversion. ?(VT) and m(min) generally affect forest height inversion more than ?(GT), and the concurrence of them brought severe overestimation to RVoG inversions (root-mean-square error (RMSE) ranges from 7.6 to 18.8 m). Stepwise comparisons show that compensating for each of ?(GT), ?(VT), and m(min) could improve the inversion accuracy further. The proposed multibaseline inversion simultaneously solved all three problems and produced the best accuracy (RMSE of 3.4 m), and it has a stable performance for another two more different multibaseline datasets, producing similar inversion accuracies (the RMSE of 3.3 and 3.6 m). The additional experiment using BIOSAR 2007 datasets with varied temporal baselines of 0, 30, and 56 days demonstrated that the proposed method has stability against temporal decorrelation. Consequently, the proposed method improved both the accuracy and robustness of forest height inversion.