scholarly journals Estimating cover fraction from TLS return intensity in coniferous and broadleaved tree shoots

Silva Fennica ◽  
2021 ◽  
Vol 55 (4) ◽  
Author(s):  
Daniel Schraik ◽  
Aarne Hovi ◽  
Miina Rautiainen
Keyword(s):  
Leaf Area ◽  
Laser Scanning ◽  
Forest Canopy ◽  
Point Clouds ◽  
Laser Beams ◽  
Experimental Calibration ◽  
Area Density ◽  
Leaf Area Density ◽  
Calibration Measurement ◽  
Lidar Return

Terrestrial laser scanning (TLS) provides a unique opportunity to study forest canopy structure and its spatial patterns such as foliage quantity and dispersal. Using TLS point clouds for estimating leaf area density with voxel-based methods is biased by the physical dimensions of laser beams, which violates the common assumption of beams being infinitely thin. Real laser beams have a footprint size larger than several millimeters. This leads to difficulties in estimating leaf area density from light detection and ranging (LiDAR) in vegetation, where the target objects can be of similar or even smaller size than the beam footprint. To compensate for this bias, we propose a method to estimate the per-pulse cover fraction, defined as the fraction of laser beams’ footprint area that is covered by vegetation targets, using the LiDAR return intensity and an experimental calibration measurement. We applied this method to a Leica P40 single-return instrument, and report our experimental results. We found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage. We further discuss limitations of our method that stem from unknown target properties that influence the LiDAR return intensity and highlight potential ways to overcome the limitations and manage the remaining uncertainty. Our method’s output, the per-beam cover fraction, may be useful in a weight function for methods that estimate leaf area density from LiDAR point clouds.

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.

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.

scholarly journals Estimating Changes in Leaf Area, Leaf Area Density, and Vertical Leaf Area Profile for Mango, Avocado, and Macadamia Tree Crowns Using Terrestrial Laser Scanning

2018 ◽  
Vol 10 (11) ◽  
pp. 1750 ◽  
Author(s):  
Dan Wu ◽  
Stuart Phinn ◽  
Kasper Johansen ◽  
Andrew Robson ◽  
Jasmine Muir ◽  
...  
Keyword(s):  
Leaf Area ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Individual Tree ◽  
Healthy Tree ◽  
Area Density ◽  
Tree Crowns ◽  
Vertical Leaf ◽  
Leaf Area Density ◽  
Mango Tree

Vegetation metrics, such as leaf area (LA), leaf area density (LAD), and vertical leaf area profile, are essential measures of tree-scale biophysical processes associated with photosynthetic capacity, and canopy geometry. However, there are limited published investigations of their use for horticultural tree crops. This study evaluated the ability of light detection and ranging (LiDAR) for measuring LA, LAD, and vertical leaf area profile across two mango, macadamia and avocado trees using discrete return data from a RIEGL VZ-400 Terrestrial Laser Scanning (TLS) system. These data were collected multiple times for individual trees to align with key growth stages, essential management practices, and following a severe storm. The first return of each laser pulse was extracted for each individual tree and classified as foliage or wood based on TLS point cloud geometry. LAD at a side length of 25 cm voxels, LA at the canopy level and vertical leaf area profile were calculated to analyse tree crown changes. These changes included: (1) pre-pruning vs. post-pruning for mango trees; (2) pre-pruning vs. post-pruning for macadamia trees; (3) pre-storm vs. post-storm for macadamia trees; and (4) tree leaf growth over a year for two young avocado trees. Decreases of 34.13 m2 and 8.34 m2 in LA of mango tree crowns occurred due to pruning. Pruning for the high vigour mango tree was mostly identified between 1.25 m and 3 m. Decreases of 38.03 m2 and 16.91 m2 in LA of a healthy and unhealthy macadamia tree occurred due to pruning. After flowering and spring flush of the same macadamia trees, storm effects caused a 9.65 m2 decrease in LA for the unhealthy tree, while an increase of 34.19 m2 occurred for the healthy tree. The tree height increased from 11.13 m to 11.66 m, and leaf loss was mainly observed between 1.5 m and 4.5 m for the unhealthy macadamia tree. Annual increases in LA of 82.59 m2 and 59.97 m2 were observed for two three-year-old avocado trees. Our results show that TLS is a useful tool to quantify changes in the LA, LAD, and vertical leaf area profiles of horticultural trees over time, which can be used as a general indicator of tree health, as well as assist growers with improved pruning, irrigation, and fertilisation application decisions.

scholarly journals Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties

2018 ◽  
Vol 10 (10) ◽  
pp. 1580 ◽  
Author(s):  
Maxime Soma ◽  
François Pimont ◽  
Sylvie Durrieu ◽  
Jean-Luc Dupuy
Keyword(s):  
Leaf Area ◽  
Forest Canopy ◽  
Voxel Size ◽  
Area Density ◽  
Terrestrial Lidar ◽  
Leaf Area Density ◽  
Physiological Processes ◽  
Gap Fraction ◽  
Vegetation Heterogeneity ◽  
Reference Measurements

Reliable measurements of the 3D distribution of Leaf Area Density (LAD) in forest canopy are crucial for describing and modelling microclimatic and eco-physiological processes involved in forest ecosystems functioning. To overcome the obvious limitations of direct measurements, several indirect methods have been developed, including methods based on Terrestrial LiDAR scanning (TLS). This work focused on various LAD estimators used in voxel-based approaches. LAD estimates were compared to reference measurements at branch scale in laboratory, which offered the opportunity to investigate in controlled conditions the sensitivity of estimations to various factors such as voxel size, distance to scanner, leaf morphology (species), type of scanner and type of estimator. We found that all approaches to retrieve LAD estimates were highly sensitive to voxel size whatever the species or scanner and to distance to the FARO scanner. We provided evidence that these biases were caused by vegetation heterogeneity and variations in the effective footprint of the scanner. We were able to identify calibration functions that could be readily applied when vegetation and scanner are similar to those of the present study. For different vegetation and scanner, we recommend replicating our method, which can be applied at reasonable cost. While acknowledging that the test conditions in the laboratory were very different from those of the measurements taken in the forest (especially in terms of occlusion), this study revealed existence of strong biases, including spatial biases. Because the distance between scanner and vegetation varies in field scanning, these biases should occur in a similar manner in the field and should be accounted for in voxel-based methods but also in gap-fraction methods.

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

2019 ◽  
Vol 11 (13) ◽  
pp. 1580 ◽  
Author(s):  
François Pimont ◽  
Maxime Soma ◽  
Jean-Luc Dupuy
Keyword(s):  
Leaf Area ◽  
Point Clouds ◽  
Tree Canopy ◽  
New Approach ◽  
Area Density ◽  
Leaf Area Density ◽  
Previous Formulation ◽  
Lad Estimation ◽  
New Formulation ◽  
Correction Terms

The spatial distribution of Leaf Area Density (LAD) in a tree canopy has fundamental functions in ecosystems. It 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 of these methods and showed that the bias-corrected Maximum Likelihood Estimator was the most efficient. However, it ignored (i) wood volumes, (ii) vegetation sub-grid clumping, (iii) the instrument effective footprint, and (iv) was limited to a single viewpoint. In practice, retrieving LAD is not straightforward, because vegetation is not randomly distributed in sub-grids, beams are divergent, and forestry plots are sampled from more than one viewpoint to mitigate occlusion. In the present article, we extend the previous formulation to (i) account for both wood volumes and hits, (ii) rigorously include correction terms for vegetation and instrument characteristics, and (iii) integrate multiview data. Two numerical experiments showed that the new approach entailed reduction of bias and errors, especially in the presence of wood volumes or when multiview data are available for poorly-explored volumes. In addition to its conciseness, completeness, and efficiency, this new formulation can be applied to multiview TLS—and also potentially to UAV LiDAR scanning—to reduce errors in LAD estimation.

scholarly journals Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem

2019 ◽  
Vol 433 ◽  
pp. 364-375 ◽  
Author(s):  
Aaron G. Kamoske ◽  
Kyla M. Dahlin ◽  
Scott C. Stark ◽  
Shawn P. Serbin
Keyword(s):  
Leaf Area ◽  
Forest Ecosystem ◽  
Airborne Lidar ◽  
Broadleaf Forest ◽  
Area Density ◽  
Leaf Area Density

scholarly journals STUDY ON INDIRECT ESTIMATING LEAF AREA DENSITY

2006 ◽  
Vol 71 (603) ◽  
pp. 111-117
Author(s):  
Ai KADAIRA ◽  
Harunori YOSHIDA ◽  
Daisuke MURAKAMI ◽  
Mamiko ITOU
Keyword(s):  
Leaf Area ◽  
Area Density ◽  
Leaf Area Density

Effect of sward structure of two tropical grasses with contrasting canopies on light distribution, net photosynthesis and size of bite harvested by grazing cattle

1982 ◽  
Vol 33 (2) ◽  
pp. 187 ◽  
Author(s):  
MM Ludlow ◽  
TH Stobbs ◽  
R Davos ◽  
DA Charles-Edwards
Keyword(s):  
Leaf Area ◽  
Growth Regulators ◽  
Light Distribution ◽  
Trimethylammonium Chloride ◽  
Tropical Pastures ◽  
Area Density ◽  
Tropical Grasses ◽  
Bite Size ◽  
Leaf Area Density ◽  
Grazing Cattle

Our aim was to determine whether increasing the sward density of tropical pastures, for the purpose of enhancing the size of bite harvested by grazing cattle, would reduce yield by affecting light distribution andcanopy photosynthesis. The growth regulators (2-chloroethy1)trimethylammonium chloride (CCC) and gibberillic acid (GA) were used to alter the leaf area density of the tussock-forming grass Setavia sphacelata and of the sward-forming grass Digitaria decumbens. GA increased plant height, the length of stem internodes, and the size of bite harvested by cattle. On the other hand, CCC decreased canopy height, and increased leaf area density and bite size. The variation of leaf area density, investigated experimentally by using growth regulators (5-25 m-1) and theoretically by simulation modelling (5-40 m-1), had no significant effect on either leaf or canopy photosynthetic characteristics. Hence we believe that there would be a negligible reduction in yield of these tropical grasses if their leaf area densities were increased up to a value of 40 m-1, which exceeds those of temperate pastures. Such increases in leaf area density may increase animal production from tropical pastures where bite size limits daily intake of forage. The agricultural implications of the findings are discussed.

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