Conference Agenda

This study proposes a sub-canopy terrain extraction method based on the statistical characteristics of interferometric phase height histograms, using spaceborne L-band bistatic InSAR data acquired by China’s Lutan-1 system. The few-look InSAR phase height histogram reveals the vertical structure of volume scatterers, where the lower-height peaks correspond to ground scattering and the higher components reflect canopy scattering. By analyzing the statistical distribution of the histogram, a ground finding approach based on the histogram is developed to estimate the digital terrain model (DTM) without relying on external data for calibration. The method exploits both global and local statistical parameters of the phase height histogram to automatically separate sub-canopy and canopy scattering components. Experiments were conducted across multiple forest sites with varying canopy types (both temperate and tropical) and complex terrain conditions using Lutan-1 bistatic InSAR observations. The results demonstrate that the retrieved DTM shows strong agreement with spaceborne LiDAR-derived DTM (GEDI and ICESat-2/ATLAS), while the corresponding forest height estimates achieve the accuracy of a few meters. These findings validate the effectiveness of the proposed phase height histogram-based approach for automated and accurate forest height and DTM inversion without using external lidar data. This approach shows great potential for large-scale forest monitoring and surveying underlying terrain, serving as a complementary technique to other multi-polarization (PolInSAR) and/or multi-baseline (TomoSAR) methods for mapping forest vertical structure (e.g., ESA’s BIOMASS mission).