Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning

Forests are complex, multi-layered ecosystems mainly comprising an overstory, understory, and soil. Radiative transfer simulations of these forests underpin the theoretical framework for retrieving forest parameters; however, the understory has often been neglected due to limitations in data acquisition technology. In this study, we assessed the contribution of the understory to canopy reflectance in a temperate broadleaf forest by comparing simulated bidirectional reflectance factor (BRF) differences between forest scenes with and without the understory. These scenes were reconstructed through voxel-based, boundary-based, and ellipsoid-based approaches respectively based on the multi-layered point cloud data acquired via combining unmanned aerial vehicle (UAV) and backpack laser scanning. The results show that the understory influences the simulated BRF across all three forest scene reconstruction approaches, suggesting that canopy reflectance signals can be used to evaluate the understory information, which provides a theoretical foundation for the feasibility of retrieving understory parameters via remote sensing. The understory increases BRF by 80% in shaded regions beneath the overstory in the red and NIR bands, and can increase BRF by 40% in the NIR band for voxel-based and ellipsoid-based forest scenes. Conversely, it reduces the simulated BRF in sunlit soil areas in the red band. Among the three forest reconstruction methods, the canopy reflectance simulation using the boundary-based model can consistently project the most understory information. Notably, the findings also indicate that the reflectance of the forest canopy definitely capture less understory vegetation information as the simulation resolution decreases, for instance, as the simulated resolution decreased from 1 m to 30 m, the absolute difference in the red band between the multi-layered BRF and L50 BRF decreased from 23.93% to 10.22% when using the boundary-based approach. It implies that higher resolution remote sensing observations are more advantageous for the retrieval of understory parameters. This study provides a successful case for modeling the multi-layered forest structure in natural temperate broadleaf forests, and even offers a theoretical reference for facilitating the retrieval of biochemical and biophysical information from the understory by remote sensing.