基于多源遥感数据及几何光学模型的森林郁闭度估测

Estimation of Forest Canopy Closure based on Multi-source Remote Sensing Data and Geometric Optical Model

森林冠层郁闭度(Forest Canopy Closure,FCC)是评估森林资源的重要因素,准确估算森林郁闭度对森林经营和管理具有重要意义。基于Li-Strahler几何光学模型,无人机激光雷达和高分六号宽幅(GF-6 Wide Field of View,GF-6 WFV)数据估测森林郁闭度,并针对混合像元的问题提出了一种可靠的方法。首先,利用无人机激光雷达衍生的高精度森林结构参数计算无人机飞行覆盖区域的光照背景分量。然后,利用连续最大角凸锥(Sequential Maximum Angle Convex Cone,SMACC)算法及线性光谱分解模型对GF-6 WFV进行混合像元分解,确定研究区最优场景分量。最后,利用Li-Strahler几何光学模型估测研究区域森林冠层郁闭度,并利用野外样地实测数据进行精度验证。结果表明:估测郁闭度与实测郁闭度之间的决定系数(R^(2))为0.6928,均方误差根(RMSE)为0.0594,总体精度为93.4%,Li-Strahler几何光学模型可以有效的在森林郁闭度反演中发挥作用。

Forest canopy closure is an important factor in evaluating forest resources and accurate estimation of forest canopy closure is of great significance to forest management.Based on Li-Strahler geometric optics model,we estimated the forest canopy closure using Unmanned Aerial Vehicle(UAV)LiDAR and GF-6 WFV data.And in order to find a way out of the problem of mixed pixels,a reliable method was proposed.Firstly,the sunlit background component within the coverage of UAV LiDAR was calculated by using the high-precision forest structure parameters derived from UAV LiDAR.Then,the SMACC algorithm and linear spectral decomposition model were used for mixed pixel decomposition of GF-6 WFV and to determine the optimal scene component in the study area.Finally,the forest canopy closure in the study area was estimated by Li-Strahler geometric optical model,and the accuracy was verified by the measured data of field sample plots.The results showed that the determination coefficient(R^(2))between the estimated canopy closure and the measured canopy closure is 0.6928,the Root Mean Square Error(RMSE)is 0.0594,and the overall accuracy is 93.4%.Li-Strahler geometric optical model can effectively play a role in the inversion of forest canopy closure.