激光雷达辅助的样地调查单木定位

LiDAR based individual tree localization for sample plot inventory

【目的】利用具有高扫描频率的线阵激光雷达辅助地面验证过程进行单木定位,快速、准确地对应样地观测结果与地面验证数据,为精准林业调查提供技术支持。【方法】以中山大学珠海校区内的人工林为研究对象,在地面验证每木调查过程中,借助线阵扫描激光雷达(本文中将其定义为监测激光雷达)辅助单木定位,首先解决背包式与监测激光雷达点云配准的问题,获取样地单木位置基准底图;然后基于背景差法,利用监测激光雷达实时追踪样地动态目标,获取地面调查人员的位置信息,并结合背包式激光雷达获取的单木位置底图,间接判断地面验证人员所测单木的位置,进而实现样地观测结果与地面验证每木调查数据的对应。【结果】对于两块不同条件的样地数据,背包式激光雷达与监测激光雷达点云粗配准均方根误差均小于0.2 m,远小于样地立木间最小间距,满足对应的要求;利用本研究的动态目标追踪和对应方法,以追踪到的地面调查人员位置点为种子点,通过最邻近搜索获取基准底图中与种子点最邻近的单木位置,实现样地观测数据与地面验证每木调查数据对应,对应准确率高于95%,平均每帧序列点云处理时间小于0.1 s,可以达到实时性的要求。【结论】本研究提出的方法−利用激光雷达在地面验证每木调查过程中辅助单木定位,可以提高样地观测结果与地面验证数据对应的精度和效率,有助于推动精准林业调查技术的进步。

[Objective]The LiDAR with high scanning frequency was used to assist the ground verification process in individual tree localization,quickly and accurately corresponding to the sample plot observation results and ground verification data,aiming to provide technical support for precision forestry survey.[Method]Taking the planted forest in Sun Yat-sen University as the research object,with the help of laser pairs LiDAR with high scanning frequency(defined as monitor LiDAR)to assist tree localization during the ground verification of individual tree inventory,we firstly solved the problem of registration with backpack and monitoring point clouds,and obtained the base map of individual tree localization in sample plots;then,based on the method of background difference,the monitor LiDAR was used to track the dynamic target in real time and obtain its positions.Combined with the individual tree localization base map,the position of the individual tree measured by the ground investigator was judged indirectly,so as to realize the correspondence between the sample plot observation and the validation data.[Result]Using our method to register the backpack and monitor point clouds,RMSE of coarse registration was all less than 0.2 m,and which was less than the minimum spacing of standing trees and met the corresponding requirements;using the dynamic target tracking and corresponding method in this paper,taking the positions of investigators as seed points,the serial number of tree which was closest to the seed points in the base map was obtained through the nearest search,so as to realize the data correspondence,its accuracy was higher than 95%,the average processing time of per frame was less than 0.1 s,which met the requirements of real-time.[Conclusion]Our method proposed in this paper uses LiDAR to assist tree localization in the process of ground verification,which can improve the accuracy and efficiency of correspondence to sample plot observation results and verification data,and helps to promote the development of precision forestry inventory technology.