基于LiDAR点云的单棵树木提取方法研究

Research on the Method of Extracting Single Tree from Lidar Point

摘要:

森林资源作为人类赖以生存的自然资源,是地球上最重要的资源之一,而衡量森林资源的指标不再局限于对森林面积的测量,准确的森林单木信息的获取对于进一步评估森林生态系统的生物物理过程及生物量估算具有重要意义。目前,对单棵树木的信息提取已成为森林精确遥感的热点之一。对基于LiDAR点云数据的植被信息提取的研究大多集中在对成片的林地信息提取,而激光雷达数据对单木冠形边缘的刻画能力受林分密度的影响较大。针对单木信息提取的研究并不多见或算法不足的现状,利用激光雷达点云数据,进行了单棵树提取方法的研究。基于圆检测的理论,检测局部极值点,计算其他点到中心点的距离,通过聚类,提取了单棵树的位置、树高及胸径信息。采用吉林省长春市城区林区的LiDAR点云数据进行了自动提取的实验,并利用同区的航空影像进行了检验；实验结果表明,该方法具有较好的实用价值与普适性,单木提取的精度可达到90%以上。

Abstract:

Forest resources, as the natural resources which the human beings rely on,is one of the most important resource on earth. The index of forest resources is no longer limited to the measurement of forest area, but the single tree information,Which is significant for the further evaluation of biophysical process of the forest ecosystem and biomass estimation . At present, the extraction of single tree information has become a hot topic of forest precision remote sensing. The research of vegetation information extraction which based on LiDAR point cloud data is mostly focused on the extraction of large-scale forest land information,because LiDAR data’s description ability on the edge of Single tree crown is strongly influenced on the stand density, In terms of the phenomenon which research of Single tree information extraction is rare, This paper studied the method of extracting single tree from Lidar Point Cloud. Based on the circle detection, regarded height maximum value as the center, calculated the distance from other points to the center, and extracted the information of single tree’s location, height and DBH by clustering. The lidar point cloud of Changchun city forest were used to do the experiments in this paper, and the aviation image in the same place were used to inspect it in the same time. The test result demonstrates the extraction precision was above 90 percent,which has the better practical value and universality.