基于无人机激光点云的单木特征提取技术在地形勘测中的应用

Single tree feature extraction technology based on UAV Lidar Application in terrain survey

森林资源在维护生态平衡,保护生物多样性,促进经济发展和维持社会文化价值等方面具有重要作用。树木高度是反映森林生产力和健康的重要结构参数,同时也是影响郁闭度高的区域地形图精度的重要因素。随着无人机技术和激光雷达技术的发展,无人机机载激光雷达技术成为森林资源调查的重要手段。本文应用无人机机载激光雷达获取激光点云数据,并对激光点云数据进行处理得到冠层高度模型,进而使用分水岭算法进行单木分割和特征提取,最后基于先验知识对树高和冠幅面积进行了拟合,得到了较好的拟合模型。经验证,激光点云数据符合精度要求,拟合模型R^(2)=0.62,拟合效果较好。本研究为后续进行树高预测,进而提高植被郁闭度高区域地形图精度的相关研究奠定了基础。

Forest resources play an important role in maintaining ecological balance,protecting biodiversity,promoting economic development,and preserving social and cultural values.Tree height is a crucial structural parameter that reflects forest productivity and health,and it also affects the accuracy of topographic maps in densely vegetated areas.With the advancement of unmanned aerial vehicle(UAV)and LiDAR technology,UAV-borne LiDAR has become an important tool for forest resource surveys.In this study,we employed UAV-borne LiDAR to acquire point cloud data and processed it to generate a canopy height model.Subsequently,the watershed algorithm was utilized for individual tree segmentation and feature extraction.Finally,based on prior knowledge,we fitted tree height and crown area,obtaining a well-fitted model.The accuracy of the LiDAR point cloud data met the requirements,and the fitted model showed a good fit with an R^(2) value of 0.62.This research provides a foundation for subsequent studies on tree height prediction and improving the accuracy of topographic maps in densely vegetated areas.