目前大部分植被辐射传输模型在模拟太阳辐射与植被之间的相互作用过程时，将植物结构进行了简化，只保留了叶片的结构和空间分布特征，而忽略了木质元素（枝干等）对冠层反射特性的影响。计算机模拟模型LESS能够充分考虑植被的多种组分光谱和结构特征，精确模拟植被冠层内部的光散射和辐射过程。本文以地面实测数据为基础，发展了以单木为基本单元的复杂森林三维场景重建基本流程；并在重建森林场景基础上，利用计算机模拟模型LESS模拟森林三维场景反射率，对比分析了森林木质元素对冠层反射率的影响。结果表明，忽略木质元素会引起植被冠层反射率模拟的偏差，特别是在近红外波段，在不同叶面积指数（LAI）下，其相对偏差都在40%以上。高空间分辨率是一个会突出木质元素影响的重要因素，随着空间分辨率提高，偏差也随之增大。不同等级枝干结构均对冠层反射率产生影响，即使忽略最小分枝也会引起17.7%（近红外）的估计误差。因此，在进行定量遥感研究中，必须考虑到忽略木质元素引起的偏差，即使是高LAI森林也无法忽视木质元素的影响。特别是在高分辨率遥感图像中，传统的以统计特征代替三维结构分布的辐射传输模型已经无法满足精度的要求。

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.