A Method for Forest Canopy Height Inversion Based on UAVSAR and Fourier–Legendre Polynomial—Performance in Different Forest Types

Abstract

Mapping forest canopy height at large regional scales is of great importance for the global carbon cycle. Polarized interferometric synthetic aperture radar is an efficient and irreplaceable remote sensing tool. Developing an efficient and accurate method for forest canopy height estimation is an important issue that needs to be addressed urgently. In this paper, we propose a novel four-stage forest height inversion method based on a Fourier–Legendre polynomial (FLP) with reference to the RVoG three-stage method, using the multi-baseline UAVSAR data from the AfriSAR project as the data source. The third-order FLP is used as the vertical structure function, and a small amount of ground phase and LiDAR canopy height is used as the input to solve and fix the FLP coefficients to replace the exponential function in the RVoG three-stage method. The performance of this method was tested in different forest types (mangrove and inland tropical forests). The results show that: (1) in mangroves with homogeneous forest structure, the accuracy based on the four-stage FLP method is better than that of the RVoG three-stage method. For the four-stage FLP method, R2 is 0.82, RMSE is 6.42 m and BIAS is 0.92 m, while the R2 of the RVoG three-stage method is 0.77, RMSE is 7.33 m, and bias is −3.49 m. In inland tropical forests with complex forest structure, the inversion accuracy based on the four-stage FLP method is lower than that of the RVoG three-stage method. The R2 is 0.50, RMSE is 11.54 m, and BIAS is 6.53 m for the four-stage FLP method; the R2 of the RVoG three-stage method is 0.72, RMSE is 8.68 m, and BIAS is 1.67 m. (2) Compared to the RVoG three-stage method, the efficiency of the four-stage FLP method is improved by about tenfold, with the reduction of model parameters. The inversion time of the FLP method in a mangrove forest is 3 min, and that of the RVoG three-stage method is 33 min. In an inland tropical forest, the inversion time of the FLP method is 2.25 min, and that of the RVoG three-stage method is 21 min. With the application of large regional scale data in the future, the method proposed in this study is more efficient when conditions allow.

Vegetation height fusion inversion algorithm based on RVoG model

“…The RVoG (random volume over ground) model proposed in Reference [10,11] simplifies the scattering scene of forest vegetation into a two-layer scattering problem composed of ground surface and vegetation layer. The first layer considers the surface scattering component contributed by the surface layer, including the surface scattering component and the dihedral angle scattering component caused by the ground-trunk structure, and assumes that the surface layer is flat, and its scattering center is fixed at z0.…”