Sampling gap fraction and size for estimating leaf area and clumping indices from hemispherical photographs

Hemispherical photography is becoming a popular technique for gap fraction measurements to characterize biophysical parameters and solar radiation in plant canopies. One of the crucial steps in the measurement of canopy gap fraction using hemispherical photography is determining the resolution of the sampling grid. In this work, the effects of varying resolutions of sampling grids by modifying the angle widths of zenithal annuli and azimuthal sectors were evaluated for leaf area and clumping indices computations. Sensitivity analysis was performed to test these effects using artificial photographs simulating ideal canopies with varying leaf area index and aggregation levels of foliage elements. Contrasting forest types, including natural tropical cloud forest and exotic plantations, were tested as real canopies. Results indicate that leaf area and clumping indices estimates are significantly affected by the variation of sampling grids. A new approach to solve the problem of null-gap segments, obscured completely by foliage, is proposed. However, the determination of optimal combinations of zenithal annuli and azimuthal sector angular widths that suit all canopy types remains a difficult practical problem that is often overlooked. Finally, theoretically sound gap fraction and size sampling regions were demonstrated for reliable estimates of canopy biophysical parameters.

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On improving the accuracy of digital hemispherical photography measurements of seasonal leaf area index variation in deciduous broadleaf forests

Canadian Journal of Forest Research ◽

10.1139/cjfr-2014-0351 ◽

2015 ◽

Vol 45 (6) ◽

pp. 721-731 ◽

Cited By ~ 8

Author(s):

Zhili Liu ◽

Xingchang Wang ◽

Jing M. Chen ◽

Chuankuan Wang ◽

Guangze Jin

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Seasonal Changes ◽

Optical Methods ◽

Hemispherical Photography ◽

Area Index ◽

Clumping Index ◽

Area Variation ◽

Major Factors

Optical methods have been widely used to estimate seasonal changes of the leaf area index (LAI) in forest stands because they are convenient and effective; however, their accuracy in deciduous broadleaf forests has rarely been evaluated. We estimate the seasonal changes in the LAI by combining periodic observations of leaf area variation with litter collection (LAIdir) in deciduous broadleaf forests and use these estimates to evaluate the accuracy of optical LAI measurements made using digital hemispherical photography (DHP). We also propose a method to correct DHP-derived LAI (LAIDHP) values for seasonal changes in major factors that influence the determination of LAI, including the woody to total area ratio (α), the element clumping index (ΩE, using three different methods), and the photographic exposure setting (E). Before these corrections were made, LAIDHP underestimates LAIdir by 14%–55% from 21 May to 1 October but overestimates it by 78% on 12 May and by 226% on 11 October. Although pronounced differences are observed between LAIdir and LAIDHP, they are significantly correlated (R2 = 0.85, RMSE = 0.32, P < 0.001). After considering seasonal changes in α, ΩE, and E, the accuracy of LAIDHP improves markedly, with a mean difference between the corrected LAIDHP and LAIdir of <17% in all periods. The results suggest that the proposed scheme for correcting LAIDHP is useful and effective for estimating seasonal LAI variation in deciduous broadleaf forests.

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Canopy transmittance models for estimating forest leaf area index

Canadian Journal of Forest Research ◽

10.1139/x93-319 ◽

1993 ◽

Vol 23 (12) ◽

pp. 2579-2586 ◽

Cited By ~ 26

Author(s):

Elizabeth M. Nel ◽

Carol A. Wessman

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Solar Zenith Angle ◽

Coniferous Forests ◽

Average Difference ◽

Area Index ◽

One Dimensional ◽

Gap Fraction ◽

Lambert Model

Leaf area index was estimated in old-growth and young post-fire coniferous forests in northwestern Colorado. A line quantum sensor was used to measure canopy transmittance at different solar zenith angles. Leaf area indices were estimated from canopy transmittance data according to three different models and were subsequently compared with leaf area indices derived from existing allometric equations. Of the three canopy transmittance methods evaluated, a Beer–Lambert model adjusted for diffuse light and solar zenith angle was in closest agreement with allometric leaf area index estimates (11.5% average difference), followed closely by the Beer–Lambert model (14.4% average difference). Leaf area index predicted by a one-dimensional inversion model did not agree well with allometric estimates (30.6% average difference). Differences in methods of data processing were found to have significant effects on final results. Subtraction of diffuse photosynthetically active radiation increased the leaf area indices. Calculation of leaf area index at each sampled point and determination of a final mean leaf area index approximated the allometrically derived values more closely than did derivation of leaf area index only once from an averaged gap-fraction value. Leaf area index estimates varied with sun angle.

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Extracting Leaf Area Index Using Viewing Geometry Effects - A New Perspective on High-Resolution Unmanned Aerial System Photography.

10.31220/osf.io/jcxa9 ◽

2020 ◽

Author(s):

Lukas Roth ◽

Helge Aasen ◽

Achim Walter ◽

Frank Liebisch

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Plant Ecology ◽

Growth And Yield ◽

Unmanned Aerial System ◽

Area Index ◽

Handheld Device ◽

Gap Fraction ◽

Rgb Images ◽

New Perspective

Abstract Extraction of leaf area index (LAI) is an important prerequisite in numerous studies related to plant ecology, physiology and breeding. LAI is indicative for the performance of a plant canopy and of its potential for growth and yield. In this study, a novel method to estimate LAI based on RGB images taken by an unmanned aerial system (UAS) is introduced. Soybean was taken as the model crop of investigation. The method integrates viewing geometry information in an approach related to gap fraction theory. A 3-D simulation of virtual canopies helped developing and verifying the underlying model. In addition, the method includes techniques to extract plot based data from individual oblique images using image projection, as well as image segmentation applying an active learning approach. Data from a soybean field experiment were used to validate the method. The thereby measured LAI 14 prediction accuracy was comparable with the one of a gap fraction-based handheld device (R2 of 0.92, RMSE of 0.42 m2 m2) and correlated well with destructive LAI measurements (R2 of 0.89, RMSE of 0.41 m2 m2). These results indicate that, if respecting the range (LAI ≤3) the method was tested for, extracting LAI from UAS derived RGB images using viewing geometry information represents a valid alternative to destructive and optical handheld device LAI measurements in soybean. Thereby, we open the door for automated, high-throughput assessment of LAI in plant and crop science.

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Using Hemispherical Photography to Determine Leaf Area Index of Landscape Trees in Urban Green Space of Dongguan, South China

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.955-959.4034 ◽

2014 ◽

Vol 955-959 ◽

pp. 4034-4038

Author(s):

Luo Jian Mo ◽

Wen Bin Li ◽

Yong Chang Ye ◽

Yong Wen Zhou ◽

Song Song Liu ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Green Space ◽

Urban Green Space ◽

Growth Stages ◽

Hemispherical Photography ◽

Area Index ◽

Urban Green ◽

Large Trees ◽

Landscape Trees

Transect sampling method was used to measure structural attributes of landscape trees in urban green space of three city parks and one residential greenbelt in Dongguan. Leaf area index (LAI) of the landscape trees in each urban green space was determined using hemispherical photography. Average DBH (diameter at the breast height) and CW(crown width) in Wenhua Square were the largest due to the presence of heritage large trees, while the landscape trees were species diverse in Renmin Park. A comparison of LAI in the green space gave a result in descending order: Renmin Park > Wenhua Square > Jinhuwan greenbelt > Yuanmei Park. The case of Renmin Park indicated that when a green space consisted of various structural attributes, landscape trees in different growth stages tended to have large LAI. Findings of our study suggested that a diversity of trees with potentially different LAI should be selected when planning urban green space.

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