The effects of sampling density on estimation of forest canopy closure using airborne LiDAR
Forest canopy closure describes the characteristic of ground covered by crown.It is one of the important features of forest stand structure,and can be used as an indicator of the redistribution of environment parameters such as light,water in forest stands.LiDAR data have been used directly to estimate forest canopy closure.The estimation accuracy was easily affected by sampling density,estimation method,etc.This paper generated sparse points using thinning strategy to analysis the effects of sampling density variation on the estimation accuracy of forest canopy closure.The estimation methods based on terrain-normalized point data (noted as CC-NLAS) and based on CHM (noted as CC-CHM) were also compared.The results showed that the estimation uncertainty of canopy closure increased while the sampling density deceased,and the estimation accuracy of canopy closure using CC-CHM method was higher than CC-NLAS method.
Qingwang Liu Yong Pang Kailong Hu Xiyun Mu
State Laboratory for Forest Remote Sensing and Information Techniques, Research Institute of Forest State Laboratory for Forest Remote Sensing and Information Techniques, Research Institute of Forest State Laboratory for Forest Remote Sensing and Information Techniques, Research Institute of Forest
国际会议
北京
英文
299-305
2013-10-09（万方平台首次上网日期，不代表论文的发表时间）