枝面积指数同叶面积指数一样,是重要的林分结构特征,但叶面积指数更受重视,而枝面积指数常被忽略（Weiskittel et al.,2006）。枝面积对总呼吸、光能辐射及降雨截留等多种生理生态过程具有重要意义（Bosceta1．，2003；Keim，2004）；...枝面积指数同叶面积指数一样,是重要的林分结构特征,但叶面积指数更受重视,而枝面积指数常被忽略（Weiskittel et al.,2006）。枝面积对总呼吸、光能辐射及降雨截留等多种生理生态过程具有重要意义（Bosceta1．，2003；Keim，2004）；枝面积及其垂直分布对森林生物多样性具有重要意义（Ingram et al．，1993）。由于受重视程度不够，展开更多
Accurate and rapid estimation of canopy cover(CC)is crucial for many ecological and environmental models and for forest management.Unmanned aerial vehicle-light detecting and ranging(UAV-LiDAR)systems represent a prom...Accurate and rapid estimation of canopy cover(CC)is crucial for many ecological and environmental models and for forest management.Unmanned aerial vehicle-light detecting and ranging(UAV-LiDAR)systems represent a promising tool for CC estimation due to their high mobility,low cost,and high point density.However,the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps.To alleviate the negative effects of within-crown gaps,we proposed a pit-free CHM-based method for estimating CC,in which a cloth simulation method was used to fill the within-crown gaps.To evaluate the effect of CC values and withincrown gap proportions on the proposed method,the performance of the proposed method was tested on 18 samples with different CC values(40−70%)and 6 samples with different within-crown gap proportions(10−60%).The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps(R^(2)=0.99 vs 0.98;RMSE=1.49%vs 2.2%).The proposed method was insensitive to within-crown gap proportions,although the CC accuracy decreased slightly with the increase in withincrown gap proportions.展开更多
文摘枝面积指数同叶面积指数一样,是重要的林分结构特征,但叶面积指数更受重视,而枝面积指数常被忽略（Weiskittel et al.,2006）。枝面积对总呼吸、光能辐射及降雨截留等多种生理生态过程具有重要意义（Bosceta1．，2003；Keim，2004）；枝面积及其垂直分布对森林生物多样性具有重要意义（Ingram et al．，1993）。由于受重视程度不够，
基金supported by the National Natural Science Foundation of China(grant numbers 41971380 and 41671414)Guangxi Natural Science Fund for Innovation Research Team(grant number 2019JJF50001)the Open Fund of State Key Laboratory of Remote Sensing Science(grant number OFSLRSS201920).
文摘Accurate and rapid estimation of canopy cover(CC)is crucial for many ecological and environmental models and for forest management.Unmanned aerial vehicle-light detecting and ranging(UAV-LiDAR)systems represent a promising tool for CC estimation due to their high mobility,low cost,and high point density.However,the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps.To alleviate the negative effects of within-crown gaps,we proposed a pit-free CHM-based method for estimating CC,in which a cloth simulation method was used to fill the within-crown gaps.To evaluate the effect of CC values and withincrown gap proportions on the proposed method,the performance of the proposed method was tested on 18 samples with different CC values(40−70%)and 6 samples with different within-crown gap proportions(10−60%).The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps(R^(2)=0.99 vs 0.98;RMSE=1.49%vs 2.2%).The proposed method was insensitive to within-crown gap proportions,although the CC accuracy decreased slightly with the increase in withincrown gap proportions.
