Assessment of camera focal length influence on canopy reconstruction quality

Martin Denter , Julian Frey , Teja Kattenborn , Holger Weinacker , Thomas Seifert , Barbara Koch
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Abstract

Unoccupied aerial vehicles (UAV) with RGB-cameras are affordable and versatile devices for the generation of a series of remote sensing products that can be used for forest inventory tasks, such as creating high-resolution orthomosaics and canopy height models. The latter may serve purposes including tree species identification, forest damage assessments, canopy height or timber stock assessments. Besides flight and image acquisition parameters such as image overlap, flight height, and weather conditions, the focal length, which determines the opening angle of the camera lens, is a parameter that influences the reconstruction quality. Despite its importance, the effect of focal length on the quality of 3D reconstructions of forests has received little attention in the literature. Shorter focal lengths result in more accurate distance estimates in the nadir direction since small angular errors lead to large positional errors in narrow opening angles. In this study, 3D reconstructions of four UAV-acquisitions with different focal lengths (21, 35, 50, and 85 mm) on a 1 ha mature mixed forest plot were compared to reference point clouds derived from high quality Terrestrial Laser Scans. Shorter focal lengths (21 and 35 mm) led to a higher agreement with the TLS scans and thus better reconstruction quality, while at 50 mm, quality losses were observed, and at 85 mm, the quality was considerably worse. F1-scores calculated from a voxel representation of the point clouds amounted to 0.254 with 35 mm and 0.201 with 85 mm. The precision with 21 mm focal length was 0.466 and 0.302 with 85 mm. We thus recommend a focal length no longer than 35 mm during UAV Structure from Motion (SfM) data acquisition for forest management practices.

相机焦距对冠层重建质量影响的评价
带有rgb相机的无人驾驶飞行器(UAV)是一种价格合理且用途广泛的设备,可用于生成一系列遥感产品,用于森林清查任务,例如创建高分辨率正形图和冠层高度模型。后者可用于树种鉴定、森林损害评估、冠层高度或木材储量评估等目的。除了图像重叠、飞行高度、天气条件等飞行和图像采集参数外,焦距也是影响重建质量的参数,它决定了相机镜头的开启角度。尽管焦距对森林三维重建质量的影响很重要,但在文献中却很少受到关注。较短的焦距导致较准确的距离估计在最低点方向,因为小的角度误差导致较大的位置误差在窄的开角。在这项研究中,对1公顷成熟混交林地块上4个不同焦距(21、35、50和85 mm)的无人机图像进行了三维重建,并将其与高质量地面激光扫描得出的参考点云进行了比较。较短的焦距(21和35 mm)与TLS扫描的一致性更高,因此重建质量更好,而在50 mm时,观察到质量损失,而在85 mm时,质量相当差。从点云的体素表示计算得到的f1分数在35 mm时为0.254,在85 mm时为0.201。焦距为21 mm时精度为0.466,焦距为85 mm时精度为0.302。因此,我们建议在用于森林管理实践的无人机运动结构(SfM)数据采集过程中,焦距不超过35毫米。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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