At present, Most vegetation radiative transfer models were developed on the basis of a simplified canopy structure when simulating the interaction between solar radiation and vegetation. They retain the structure and spatial distribution characteristics of leaves but ignore the influences of wood elements (such as branches) on the reflection characteristics of a canopy. LESS, as one of the computer simulation models, can fully consider the spectral and structural characteristics of various components (leaves and branches) of vegetation and accurately simulate the process of light scattering and radiation in the canopy. Thus, it can be applied to analyze the effects of wood elements on the reflectance of a forest canopy on the basis of a reconstructed realistic three dimensional (3D) forest scene.On the basis of field data, we developed a basic framework to reconstruct a 3D scene of a complex forest with single tree as basic unit. Diameter at Breast Height (DBH) was selected as the main variable to divide trees into six levels (T1—T6). The mean DBH, mean tree height, mean crown width, and mean height of branches at level were used as typical parameters to build a tree model by using OnyxTREE. When a near-real 3D forest scene was constructed, the appropriate model in the constructed single-tree library was selected with the DBH level as the standard. The computer simulation model LESS was used to simulate the reflectance of 3D scenes of forests with and without wood elements. The effects of forest wood elements on canopy reflectance were analyzed quantitatively.Ignoring the wood elements will lead to the deviation of vegetation canopy reflectance, especially in the NIR band. The relative deviation of reflectance in the NIR band is more than 40% for all scenes with different LAIs. High spatial resolution is another important factor highlighting the influences of wood elements. As the spatial resolution increases, the deviation increases. Different grades of woody structure affect canopy reflectance; even ignoring a twig will cause an estimation error of 17.7% (NIR band). The use of wooden area instead of leaf area can partially alleviate the difference in canopy reflectance caused by completely ignoring wooden elements, but it still leads to overestimation (NIR) or underestimation (visible light) of canopy reflectance.The vegetation radiative transfer models that use statistical features to replace 3D structure distribution can no longer meet the accuracy requirements of quantitative remote sensing. Hence, the deviation caused by ignoring wood elements should be considered, specially for high-resolution remote sensing images.