Comparison of UAS-Based Structure-from-Motion and LiDAR for Structural Characterization of Short Broadacre Crops
Comparison of UAS-Based Structure-from-Motion and LiDAR for Structural Characterization of Short Broadacre Crops
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DOI：
10.3390/rs13193975
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发表时间：
2021-10
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通讯作者：
Fei Zhang;A. Hassanzadeh;J. Kikkert;S. Pethybridge;J. Aardt
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作者：
Fei Zhang;A. Hassanzadeh;J. Kikkert;S. Pethybridge;J. Aardt
基于小型无人机系统(UAS)的运动结构(SfM；摄影测量)和激光雷达点云的使用在遥感领域得到了广泛的讨论。在这里，我们比较了SfM和LiDAR点云的多个方面，这些点云是在一种短作物(Snap Bean)的五个UAS飞行试验田同时收集的，以探索SfM方法在作物表型鉴定方面与LiDAR相比的表现。主要方法包括计算经预处理的点云之间的云-网距离(C2M)图，以及计算派生的数字高程模型(DEM)和作物高度模型(CHM)之间的多尺度模型-模型云比较(M3C2)距离图。我们还评估了来自CHM的作物高度和行宽，并将它们与其中一个数据集的田间测量结果进行了比较。SfM和LiDAR点云的作物高度平均均方根误差约为0.02m，行宽平均均方根误差约为0.05m。定性和定量分析证明，在相同的UAS飞行条件下，SfM方法与LiDAR方法具有可比性。然而，其测高精度在很大程度上取决于地面控制点的数量和分布。
The use of small unmanned aerial system (UAS)-based structure-from-motion (SfM; photogrammetry) and LiDAR point clouds has been widely discussed in the remote sensing community. Here, we compared multiple aspects of the SfM and the LiDAR point clouds, collected concurrently in five UAS flights experimental fields of a short crop (snap bean), in order to explore how well the SfM approach performs compared with LiDAR for crop phenotyping. The main methods include calculating the cloud-to-mesh distance (C2M) maps between the preprocessed point clouds, as well as computing a multiscale model-to-model cloud comparison (M3C2) distance maps between the derived digital elevation models (DEMs) and crop height models (CHMs). We also evaluated the crop height and the row width from the CHMs and compared them with field measurements for one of the data sets. Both SfM and LiDAR point clouds achieved an average RMSE of ~0.02 m for crop height and an average RMSE of ~0.05 m for row width. The qualitative and quantitative analyses provided proof that the SfM approach is comparable to LiDAR under the same UAS flight settings. However, its altimetric accuracy largely relied on the number and distribution of the ground control points.