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Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

机译:估算智能手机摄影测量点云的树木直径和体积

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Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion-SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m(3), for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using 'non-professional' instruments and automating estimates of dendrometric parameters.
机译:已经提出了来自主动和被动传感器的数据的三维(3D)重建的方法。尽管成本高,但激光扫描仪技术在过去几年中变得流行。由于摄影测量算法的改进(例如,来自Motion-SFM的结构),因此照片已成为3D点云的新低成本来源。在本研究中,我们使用由智能手机相机捕获的图像使用SFM计算森林图的密集点云。通过改变致密化参数(图像比例,点密度,匹配数)来产生十八点云,以便研究它们对所产生点云的质量的影响。为了估计乳房高度(D.B.H.)和茎体积的直径,我们开发了一种自动方法,从点云中提取阀杆,然后用圆筒模拟它们。结果表明,图像刻度是从点云识别和提取树木方面最有影响力的参数。与现场数据相比,从点云中建模的最佳性能具有1.9厘米和0.094米(3)的RMSE,为D.B.H.和体积分别。因此,对于森林管理和规划目的,可以使用我们的摄影测量和建模方法来测量D.B.H.,Step Volume,以及可能的其他森林库存指标,迅速和不砍伐树木。所提出的方法,使用“非专业”仪器和自动化行落参数的自动化估计来显着降低现场工作时间。

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    《Forestry》 |2020年第3期|共19页
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