scholarly journals Ground-based estimation of leaf area index and vertical distribution of leaf area density in a Betula ermanii forest

Silva Fennica ◽  
2009 ◽  
Vol 43 (5) ◽  
Author(s):  
Akihiro Sumida ◽  
Taro Nakai ◽  
Masahito Yamada ◽  
Kiyomi Ono ◽  
Shigeru Uemura ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Area Index ◽  
Area Density ◽  
Betula Ermanii ◽  
Leaf Area Density ◽  
Betula Ermanii Forest

An assessment study of three indirect methods for estimating leaf area density and leaf area index of individual trees

2020 ◽  
Vol 292-293 ◽  
pp. 108101 ◽  
Author(s):  
Shanshan Wei ◽  
Tiangang Yin ◽  
Maria Angela Dissegna ◽  
Andrew J. Whittle ◽  
Genevieve Lai Fern Ow ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Indirect Methods ◽  
Area Index ◽  
Area Density ◽  
Leaf Area Density ◽  
Assessment Study ◽  
Individual Trees

scholarly journals Estimation of maize plant height and leaf area index dynamics using an unmanned aerial vehicle with oblique and nadir photography

2020 ◽  
Vol 126 (4) ◽  
pp. 765-773 ◽  
Author(s):  
Yingpu Che ◽  
Qing Wang ◽  
Ziwen Xie ◽  
Long Zhou ◽  
Shuangwei Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Height ◽  
Large Scale ◽  
High Efficiency ◽  
Point Clouds ◽  
Phenotypic Traits ◽  
Area Index ◽  
Area Density ◽  
Leaf Area Density

Abstract 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.

Vertical distribution of leaf area in Larixoccidentalis: a comparison of two estimation methods

1989 ◽  
Vol 19 (9) ◽  
pp. 1131-1136 ◽  
Author(s):  
William R. Bidlake ◽  
R. Alan Black
Keyword(s):  
Vertical Distribution ◽  
Leaf Area Index ◽  
Normal Distribution ◽  
Leaf Area ◽  
Stand Density ◽  
Total Leaf Area ◽  
Area Index ◽  
Total Leaf ◽  
Gap Fraction ◽  
The Vertical Distribution

Total leaf-area index and the vertical distribution of leaf-area index were described for an unthinned stand (density 11 250 stems/ha) and a thinned stand (density 1660 stems/ha) of 30-year-old Larixoccidentalis Nutt. Two independent methods were used to estimate leaf-area index in each of the two stands. The first method is based on allometric relationships that are applied to stem measurements, and the second method is based on gap-fraction analysis of fisheye photographs. Leaf-area index estimates obtained by the two methods were not significantly different. The gap-fraction method provides a desirable alternative because much less fieldwork is required, however, use of this method is limited to canopies where the light-blocking elements are randomly displayed. Total leaf-area index values for the unthinned and thinned stands were 5.0 and 3.6, respectively. The vertical distribution of leaf-area index in the unthinned stand resembled a normal distribution. The vertical distribution of leaf-area index in the thinned stand would have resembled a normal distribution, except that thinning operations resulted in a truncated distribution of leaf-area index at the canopy base.

scholarly journals Accounting for Wood, Foliage Properties and Laser Effective Footprint in Estimations of Leaf Area Density from multiview-LiDAR Data

2019 ◽  
Author(s):  
Francois Pimont ◽  
Maxime Soma ◽  
Jean-Luc Dupuy
Keyword(s):  
Maximum Likelihood ◽  
Leaf Area ◽  
Point Clouds ◽  
Tree Canopy ◽  
Estimation Methods ◽  
Numerical Comparison ◽  
Area Index ◽  
Area Density ◽  
Leaf Area Density ◽  
Contact Frequency

The amount and spatial distribution of foliage in a tree canopy have fundamental functions in ecosystems as they affect energy and mass fluxes through photosynthesis and transpiration. They are usually described by the Leaf Area Index (LAI) and the Leaf Area Density (LAD), which can be measured through a variety of methods, including voxel-based methods applied to LiDAR point clouds. A theoretical study recently compared the numerical errors arising from different voxel-based estimation methods for Plant Area Density (PAD) based on Beer’s law-based, contact frequency and Maximum-Likelihood Estimation, showing that the bias-corrected Maximum Likelihood Estimator was theoretically the most efficient. However, this earlier study i) ignored wood volumes; ii) neglected vegetation clumping inside the voxel; iii) ignored instrument characteristics in terms of effective footprint, iv) was limited to a single viewpoint. In practice, retrieving LAD from PAD is not straightforward, vegetation is not randomly distributed in volumes of interest, beams are divergent and forestry plots are usually sampled from more than one viewpoint, to mitigate the effect of occlusion. In the present short communication, we extend the previous efficient formulation to actual field conditions to i) account for the presence of both wood volumes and wood hits, ii) rigorously include correction terms for vegetation and instrument characteristics, iii) integrate multiview data. A numerical comparison with other methods commonly used to combine information from different viewpoints led to error reduction, especially in poorly-explored volumes, which are frequent in actual canopies. Beyond its concision, completeness and efficiency, this new formulation -which can be applied to multiview TLS, but also UAV LiDAR scanning - can help reducing errors in LAD estimation.

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