An Improved Forest Parameters Extraction Method Applicable to Different Tree Densities from PolInSAR Data

The tree density significantly influences the penetration and signal decay of the polarimetric interferometric synthetic aperture radar (PolInSAR) signal. Therefore, it can be asserted that forest density is a crucial parameter determining the effectiveness of vegetation parameters identified from PolInSAR data. Previous forest height inversion processes often resulted in substantial errors when applied in areas with sparse or dense tree canopies. To eliminate the above disadvantages and improve the efficiency of vegetation height extraction across different tree densities, we propose introducing a correction coefficient into the forest height inversion process. Additionally, the relationship between woodland density, wave attenuation factor, and surface phase are analyzed in this paper. The effectiveness of the proposed approach significantly improved when applied to forested areas with varying tree densities and complex terrains.