Reconstruction of a large-scale realistic three-dimensional (3-D) mountain forest scene for radiative transfer simulations

ABSTRACT

The realistic three-dimensional (3D) forest scene is an important input to 3D radiative transfer simulations, which are essential for analyzing the reflective properties of forest canopies. Previous studies utilized the voxel as an essential element to reconstruct the 3D forest scene, while they mainly focused on the small flattened areas and ignored the wood components. This study introduces a novel approach for reconstructing a realistic 3D mountain forest scene by incorporating branches into the voxel crown. To determine the optimal voxel size for simulating Bidirectional Reflectance Functions (BRFs) in a temperate deciduous mountain forest, this study reconstructed the forest scene using eight different voxel sizes, ranging from 30 to 100 cm with a step of 10 cm. Two forest scenes were examined to evaluate the impact of branches on radiative transfer simulations: one with branch voxel-based scenes and one without branches. The radiative transfer simulation is conducted using an efficient Monte Carlo path-tracing algorithm and has been implemented in the LargE-Scale remote sensing data and image Simulation framework (LESS) model, facilitating high-quality, large-scale simulations of forested environments. The finding revealed that the optimal voxel size for simulating BRFs in 30 m resolution is approximately 90 cm, smaller than the 100 cm used in flat areas. This study emphasized the significant impact of branches on the BRF simulations and underscored their critical role in scene reconstruction. The impact of branches is two-fold: branches themselves increase the simulated BRFs, whereas their shadows decrease them. Moreover, the effects of branches and their shadows decrease as the voxel size increases. The simulated spectral albedo exhibits maximum deviations of 0.71% and 1.04% in the red and NIR wavebands, respectively, while remaining below 0.2% in the blue waveband. Furthermore, the study suggests that if the precise branch architecture is unknown, constructing branches of the first generation is recommended to achieve better results. Additionally, the results demonstrate that the proposed scene achieves greater accuracy and robustness when compared to both the ellipsoid-based and the boundary-based scenes. The finding of this study can help researchers to better understand the underlying mechanisms driving the reflective properties of forest canopies, which can inform future studies and improve the accuracy of forest monitoring and ecological modeling.

KEYWORDS:

• Realistic forest scene reconstruction
• branches effect
• unmanned aerial vehicle LiDAR
• mountain area

Acknowledgments

This work was supported by the National Key Research and Development Program of China (Grant No.2020YFA0608702) and National Natural Science Foundation of China (Grant No. 41631180 and Grant No. 42271398).

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of the study area are available from the first author, [Xiaohan Lin, [email protected]], upon reasonable request.

Additional information

Funding

This work was supported by the [National Key Research and Development Program of China] under Grant [number 2020YFA0608702] and [National Natural Science Foundation of China] under Grant [number 41631180, 42271398].