基于单站地面激光雷达数据的自适应胸径估计方法

Adaptive Estimation Method for Diameter at Breast Height Based on Terrestrial Laser Scanning

为了自动化地、准确地从单站地面激光雷达(TLS)数据中提取一定范围内的树木胸径,提出一种基于点云切片的圆形-椭圆自适应胸径(DBH)估计方法。对林地点云数据在胸高位置进行切片,然后对胸高切片点云进行聚类,利用圆形-椭圆自适应拟合方法对聚类结果进行树干点判别,符合圆形分布的树干点集直接用于计算树木胸径,符合椭圆分布的树干点集进行胸高位置校正之后再进行胸径计算。利用TLS在北京市东升郊野公园的人工柳树林进行样地点云数据采集,验证圆形-椭圆自适应胸径估计方法,并与单纯圆形拟合方法对比。结果显示,在扫描距离为26m的样地范围内,树木胸径估计均方根误差为1.1cm,在扫描距离为56m的样地范围内,树木胸径估计均方根误差为1.99cm,判别为椭圆分布的树木胸径估计结果平均误差比单纯圆形拟合结果降低4.7%。该方法可以快速有效地进行自适应胸径估计。

In order to automatically and accurately extract the diameter at breast height （DBH） of trees within a certain range from the single-station terrestrial laser scanning （TLS）, an adaptive circle-ellipse fitting DBH estimation method is proposed based on the point cloud slice. The forestry point cloud data at breast height is sliced, the point cloud of the slice is clustered, and the proposed method is used to distinguish whether they are trunk points. DBH of the trunk point is calculated directly when the point conforms to the circular distribution, while DBH of the trunk point is calculated after breast height position correction when the point conforms to the elliptic distribution. The artificial willows data acquired in Beijing Dongsheng Country Park is used to verify the proposed method and compare it with the simple circular fitting method. The results show that the root mean square error of estimated DBH is 1.1 cm when the scanning distance is within 26 m, and it is 1.99 cm when the scanning distance is within 56 m. For the trees regarded as elliptic distribution, the mean error of DBH estimation results is 4.70/6o lower than that of the circular fitting results. The DBH can be detected quickly and efficiently with the proposed method.