An Improved Dual-Baseline PolInSAR Method for Forest Height Estimation Based on RMoG Model

PolInSAR technique has been proved effective in mapping forest height. However, for P band repeat-pass PolInSAR data, the influence of residual ground scattering contribution and temporal decorrelation are non-negligible for forest height inversion. To resolve these two problems, we developed a dual-baseline inversion method to reduce the influence of ground scattering contribution, and then cooperated it with Random-Motion-over-Ground (RMoG) model to compensate for the influence of temporal decorrelation. The Three-stage inversion showed a severe overestimation for the whole image, producing R2 of ca. 0.4 and RMSE of ca. 7m. For near range (with $k_{z}$ larger than 0.1rad/m), the overestimation was mainly caused by ground scattering contribution, which was effectively solved by using fixed extinction method. For far range (with $k_{z}$ smaller than 0.06rad/m), the influence of ground scattering contribution seemed decreased because the fixed extinction method did not reduce the overestimation, and overestimation was mainly caused by volume temporal decorrelation. Besides, the influence of ground scattering contribution on forest height inversion seemed greater than that of temporal decorrelation. The proposed method successfully solved both of the two influences, and reduced the overestimation for both near and far range, producing the best accuracy with R2 of 0.62 and RMSE of 3.73m.