An Advanced Approach for Understory Terrain Extraction Utilizing TomoSAR and MCSF Algorithm

Abstract

The understory terrain is an essential component of forest vertical structure and ecosystem health, providing crucial insights for resource assessment and forestry surveys. This letter proposes a novel method for extracting understory terrain through forest backscattering power profiles and the modified cloth simulation filtering (MCSF) algorithm. It innovatively reconstructs synthetic aperture radar (SAR) signals into a 3-D point cloud, eliminating sidelobe signals to reduce noise while only retaining the mainlobe signals. The MCSF algorithm is subsequently utilized to extract ground and nonground points based on the vertical distribution of the mainlobe signals. The extracted ground points offer a more precise representation of actual terrain conditions. The feasibility of the method was validated utilizing airborne P-band multi baseline SAR data obtained from the Saihanba test site in Hebei Province. The outcomes clearly indicate that our approach exhibits superior correlation (0.999) and a smaller root mean square error (RMSE) (3.07 m) in comparison to conventional methods when compared with the reference digital elevation model (DEM).