研究目的
Investigating the use of a voxel-based approach to derive forest mock-ups from LiDAR data for 3D radiative transfer simulation with the DART model.
研究成果
The paper presents a voxel-based method for reconstructing 3D forest scenes from ALS data, adaptable to the DART model via the DAO tool. This method facilitates the creation of 3D scenes by directly manipulating voxel properties, though challenges remain in accurately simulating reflectance values due to unknown leaf and ground optical properties.
研究不足
The approach may underestimate tree height due to sparse ALS datasets, especially for conifer trees. Additionally, default vegetation optical properties in DART simulations may lead to inaccuracies in reflectance values.
1：Experimental Design and Method Selection:
The study uses a voxel-based approach to reconstruct 3D forest scenes from airborne LiDAR data, adapted for the DART model.
2：Sample Selection and Data Sources:
The study area is located in the Genhe Forest Reserve, with data acquired by a CAF-LiCHy system.
3：List of Experimental Equipment and Materials:
Equipment includes the CAF-LiCHy system, comprising a LiDAR (Riegl LMS-Q680i), and a push-broom hyperspectral sensor (AISA Eagle II).
4：Experimental Procedures and Operational Workflow:
Steps include ground filtering, DEM/CHM generation, point cloud normalization, LAI inversion, 3D mock-up reconstruction, and DART simulations.
5：Data Analysis Methods:
The realism of the reconstruction approach was tested by comparing DART and AISA NIR BRF orthographic images.
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