Simultaneous Estimation of Subcanopy Topography and Forest Height With Single-Baseline Single-Polarization TanDEM-X Interferometric Data Combined With ICESat-2 Data.

To address the challenge of retrieving subcanopy topography using single-baseline single-polarization TanDEM-X interferometric synthetic aperture radar (InSAR) data, we propose a novel InSAR processing framework. Our methodology begins by employing the SINC model to estimate the penetration depth (PD). Subsequently, we establish a linear relationship between PD and phase center height (PCH) to generate a wall-to-wall PCH product. To achieve this, spaceborne light detection and ranging (LiDAR) data are employed to capture the elevation bias between actual ground elevation and InSAR-derived elevation. Finally, the subcanopy topography is derived by subtracting the PCH from the conventional InSAR-based digital elevation model (DEM). Moreover, this approach enables the simultaneous estimation of forest height from single-baseline TanDEM-X data by combining the estimated PD and PCH components. The approach has been validated against airborne LiDAR scanning (ALS) data over four diverse sites encompassing different forest types, terrain conditions, and climates. The derived subcanopy topography in the boreal and hemiboreal forest sites (Krycklan and Remningstorp) demonstrated notable improvement in accuracy. Additionally, the winter acquisitions outperformed the summer ones in terms of inversion accuracy. The achieved root-mean-square errors (RMSEs) for the winter scenarios were 2.45 m and 3.83 m, respectively, representing a 50% improvement over the InSAR-based DEMs. The forest heights are also close to the ALS measurements, with RMSEs of 2.70 m and 3.33 m, respectively. For the Yanguas site in Spain, characterized by rugged terrain, subcanopy topography in forest areas was estimated with an accuracy of 4.27 m, a 35% improvement over the original DEM. For the denser tropical forest site, only an average elevation bias could be corrected.