利用具有倾斜和正摄影像的无人机估算玉米植株高度和叶面积指数动态。
Estimation of maize plant height and leaf area index dynamics using an unmanned aerial vehicle with oblique and nadir photography.
机构信息
Key Laboratory of Arable Land Conservation (North China), Ministry of Agriculture, College of Resources and Environmental Sciences, China Agricultural University, Beijing, China.
Center for Crop Functional Genomics and Molecular Breeding, College of Biological Science, China Agricultural University, Beijinge China.
出版信息
Ann Bot. 2020 Sep 14;126(4):765-773. doi: 10.1093/aob/mcaa097.
BACKGROUND AND AIMS
High-throughput phenotyping is a limitation in plant genetics and breeding due to large-scale experiments in the field. Unmanned aerial vehicles (UAVs) can help to extract plant phenotypic traits rapidly and non-destructively with high efficiency. The general aim of this study is to estimate the dynamic plant height and leaf area index (LAI) by nadir and oblique photography with a UAV, and to compare the integrity of the established three-dimensional (3-D) canopy by these two methods.
METHODS
Images were captured by a high-resolution digital RGB camera mounted on a UAV at five stages with nadir and oblique photography, and processed by Agisoft Metashape to generate point clouds, orthomosaic maps and digital surface models. Individual plots were segmented according to their positions in the experimental design layout. The plant height of each inbred line was calculated automatically by a reference ground method. The LAI was calculated by the 3-D voxel method. The reconstructed canopy was sliced into different layers to compare leaf area density obtained from oblique and nadir photography.
KEY RESULTS
Good agreements were found for plant height between nadir photography, oblique photography and manual measurement during the whole growing season. The estimated LAI by oblique photography correlated better with measured LAI (slope = 0.87, R2 = 0.67), compared with that of nadir photography (slope = 0.74, R2 = 0.56). The total number of point clouds obtained by oblique photography was about 2.7-3.1 times than those by nadir photography. Leaf area density calculated by nadir photography was much less than that obtained by oblique photography, especially near the plant base.
CONCLUSIONS
Plant height and LAI can be extracted automatically and efficiently by both photography methods. Oblique photography can provide intensive point clouds and relatively complete canopy information at low cost. The reconstructed 3-D profile of the plant canopy can be easily recognized by oblique photography.
背景与目的
高通量表型分析是植物遗传学和育种中的一个限制因素，因为在田间进行大规模实验。无人机 (UAV) 可以帮助快速、非破坏性地提取植物表型特征，并且效率很高。本研究的总体目的是通过无人机的正射和倾斜摄影来估计动态植物高度和叶面积指数 (LAI)，并比较这两种方法建立的三维 (3-D) 冠层的完整性。
方法
使用安装在无人机上的高分辨率数字 RGB 相机在五个阶段进行正射和倾斜摄影，通过 Agisoft Metashape 处理生成点云、正射镶嵌图和数字表面模型。根据实验设计布局中的位置对各个地块进行分割。通过参考地面方法自动计算每个自交系的高度。通过 3-D 体素方法计算 LAI。将重建的冠层切成不同的层，比较从倾斜和正射摄影获得的叶面积密度。
主要结果
在整个生长季节，正射摄影、倾斜摄影和手动测量的植物高度之间存在良好的一致性。与正射摄影相比，倾斜摄影估算的 LAI 与实测 LAI 的相关性更好（斜率=0.87，R2=0.67）。通过倾斜摄影获得的点云总数约为正射摄影的 2.7-3.1 倍。通过正射摄影计算的叶面积密度比通过倾斜摄影获得的密度小得多，尤其是在靠近植物基部的地方。
结论
两种摄影方法都可以自动、高效地提取植物高度和 LAI。倾斜摄影可以以较低的成本提供密集的点云和相对完整的冠层信息。通过倾斜摄影可以轻松识别植物冠层的重建 3-D 轮廓。
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