Underlying Terrain and Forest Height Retrieval based on Lutan-1 L-Band Bistatic InSAR Phase-Height Histograms

This study presents a scalable framework for retrieving sub-canopy terrain elevations and forest canopy heights based on phase-height histograms constructed from few-look L-band bistatic InSAR data acquired by China’s Lutan-1 mission, with forest canopy height directly derived from the uppermost position of the histogram. The proposed method was evaluated over several representative forested regions in China, including Jianfengling National Forest Park (Hainan Province), Saihanba National Forest Park (Hebei Province), and the Northeast China Tiger and Leopard National Park (Jilin Province). The approach classifies phase-height histograms into four distinct types based on their statistical and morphological characteristics, corresponding to different scattering scenarios. For each type, type-specific strategies are applied to extract ground-related features, enabling robust estimation of the digital terrain model (DTM), while forest canopy height is derived from the vertical distribution of scattering. To improve accuracy in areas with complex scatterers, such as wetlands or water bodies, a supplementary regression based on backscatter intensity is employed to correct anomalously low height estimates. Validation against spaceborne LiDAR (GEDI and ICESat-2/ATLAS) demonstrates that the method produces reliable terrain and canopy height products across diverse forest types, ranging from tropical montane forests to temperate plantations and mixed natural forests. These results demonstrate that the proposed phase-height histogram-based approach can reliably and automatically retrieve forest canopy height and DTM without requiring any additional auxiliary data (e.g., LiDAR). This highlights that phase-height histograms provide a practical, reproducible, and scalable tool for large-scale forest monitoring, offering a complementary approach to PolInSAR and TomoSAR techniques for ecological applications.