大青山前坡油松林高度的无人机监测研究

Height Measurement of Pinus tabulaeformis Forest in Front Slope of Daqing Mountains with Unmanned Aerial Vehicles Technology

森林生态系统是陆地生态系统的重要组成部分,树高是森林调查中最重要的因子之一。本研究通过对内蒙古呼和浩特市大青山前坡油松林进行地面控制点测量-无人机航空摄影试验获取数据,对无人机影像获取的油松林高度与野外实地测量坑底至冠层顶部的数据进行对比分析,研究结果表明:在选取测量对比的30个样本中,无人机监测高度与实际测量值绝对误差范围在0~114 cm之间,平均绝对误差12 cm,相关系数R^2为0.7059,剔除异常数据后相关系数R^2达到0.9059,通过无人机影像获取点云数据生成冠层高度模型(CHM)监测油松林高度的方法是可行的。

Forest ecological system is the most important main part of terrestrial ecosystem. Tree height is one of vital factors in the forest investigation. The research has obtained the data by unmanned aerial vehicle(UAV) aerial photogrammetry and ground control points in the front slope of Daqing Mountains, Inner Mongolia. Base on canopy height model(CHM), by using the Pix4 D, Global Mapper and ArcGIS processing platform, tree heights have been extracted from the images. The comparative analysis of the data on the height of Pinus tabulaeformis forest acquired from the UAV image and the field measurement shows that the range of the absolute error between the UAV monitoring and the actual measurement is 0~114 cm, the mean absolute error is 12 cm, the correlation coefficient R^2 is 0.7059, and the correlation coefficient R^2 reaches 0.9059 after the abnormal data are removed. It is feasible that UAV imagery is used to measure tree height. UAV technology has a wide application in forest investigation with obtaining point cloud data to form canopy height model.