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

P-band 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 (γ VT ), ground temporal decorrelation (γ 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 multi-baseline 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. γ VT and m_min generally affect forest height inversion more than γ GT , and the concurrence of them brought severe overestimation to RVoG inversions (RMSE ranges from 7.6 to 18.8 m). Stepwise comparisons show that compensating for each of γ GT , γ VT , and m_min could improve the inversion accuracy further. The proposed multi-baseline 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 multi-baseline datasets, producing similar inversion accuracies (RMSE of 3.3 and 3.6 m). The additional experiment using BIOSAR 2007 datasets with varied temporal baselines of 0 day, 30 days, 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.