以海南省五指山市4块人工桉树林共计157株桉树为例,融合背包激光雷达和机载激光雷达点云数据对桉树单木因子进行了估测,探究融合数据在森林资源调查中的适用性。估测结果与实际样地数据对比表明,融合点云数据在胸径的估测上,R²=0.982,RMSE=0.868cm;在树高的估测上,R²=0.895,RMSE=2.005m,优于只使用背包激光雷达数据获取树高精度(R²=0.835,RMSE=2.458m)。基于背包激光雷达点云数据获取的单木胸径精度较高,融合点云数据可改善单一背包点云数据对树高上的估测。

We investigated the applicability of fused data in forest resource surveys by fusing backpack LiDAR and airborne LiDAR point cloud data to estimate the single wood factor of eucalyptus trees in four eucalyptus plantations in Wuzhishan City,Hainan Province,with a total of 157 eucalyptus trees. A comparison of the results with the actual sample plots showed that the fused point cloud data had an R²=0.982 and RMSE=0.868cm for the estimation of diameter at breast height,and R²=0.895 and RMSE=2.005m for the estimation of tree height,which was better than that of the high accuracy of the tree obtained using only backpack LiDAR data (R²=0.835 and RMSE=2.458m).This study demonstrated that backpack LiDAR-based point cloud data was more accurate in obtaining single wood diameter at breast height,and that fused point cloud data could improve the estimation of tree height from single backpack point cloud data.