一般消费级无人机的树障监测精度验证

Accuracy verification of danger tree monitoring for general consumer UAV

无人机技术的发展使传统树障监测的方法变得更加数字化和便捷化。为了探究一般消费级无人机测量树高的精度问题,本文以桂林理工大学雁山校区为研究区,把无人机获取的高分辨率影像经处理后分别对比了基于数字冠层高度模型CHM和基于点云信息这两种方法提取树高的精度。试验结果表明:基于点云提取的树高平均绝对误差为12.4 cm,精度总体上优于基于数字冠层高度模型CHM的提取精度;基于CHM提取的树高小于实测高度;另外,圆形树冠的树高提取精度优于锥形树冠。两种方法测量值与真实值的相关性分别为0.97和0.98,证明了使用无人机进行树障监测的可行性。

The development of UAV technology makes the traditional method of danger tree monitoring more digital and convenient.In order to explore the accuracy of tree height measurement by general consumer UAV,this paper takes Yanshan campus of Guilin University of technology as the research area.The high-resolution images acquired by UAV were processed and compared the accuracy of extracting tree height based on the digital canopy height model(CHM)and point cloud information,respectively.The experimental results show that the mean absolute error of tree height based on point cloud extraction is 12.4 cm,which is better than that based on the digital canopy height model(CHM).The tree height extracted from CHM will be less than the measured height.In addition,the accuracy of extracting height of round crown is better than that of cone crown.The correlation between the measured and true values of the two methods was 0.97 and 0.98,respectively,which indicates that the method of danger tree monitoring by UAV is feasible.