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Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions

Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions
Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions

Indirect optical measurement techniques enable efficient and non-destructive estimation of plant area index (PAI). However, because they cannot distinguish between foliage and other canopy elements, corrections are needed to determine leaf area index (LAI), which is typically the property of interest. In this study, we investigate near-infrared digital hemispherical photography (DHP) as a means of estimating and correcting for woody material. Using data collected at a deciduous broadleaf forest site, we show that near-infrared DHP could successfully estimate effective wood area index (WAIe) and wood area index (WAI) during leaf-on conditions, providing similar mean values (WAIe = 0.88, WAI = 1.53) to those determined from visible DHP during leaf-off conditions (WAIe = 0.87, WAI = 1.38). This information was used to correct estimates of effective PAI (PAIe) and PAI, enabling effective LAI (LAIe) and LAI to be derived with low RMSD (0.33 for LAIe and 0.76 for LAI), NRMSD (12% for LAIe and 19% for LAI), and bias (−0.01 for LAIe and −0.16 for LAI). Not correcting for woody material led to overestimation of LAIe by 31% on average and 46% in the worst observed case, and the degree of overestimation was further enlarged for LAI (42% on average and 61% in the worst observed case). In agreement with previous studies, the effects of clumping and woody area were found to be partly compensatory. On average, PAIe provided a reasonable approximation of LAI without correction, though overestimation of 52% and underestimation of 20% occurred at the lowest and highest LAI values, respectively. Compared to WAIe and WAI measurement using leaf-off visible DHP, near-infrared DHP offers two crucial advantages: i) data collection can be conducted at the same time as leaf-on PAIe and PAI measurements, and ii) it is likely that the approach could provide an indirect WAIe and WAI measurement option for evergreen species.

DHP, Leaf area index (LAI), Near-infrared imagery, PAI, Wood area index (WAI)
1574-9541
Brown, Luke A.
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Morris, Harry
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Morrone, Rosalinda
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Sinclair, Morven
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Williams, Owen
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Hunt, Merryn
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Bandopadhyay, Subhajit
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Guo, Xuerui
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Akcay, Haydar
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Dash, Jadunandan
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Brown, Luke A.
6a693f08-df9e-4494-bb89-8d2897470d4a
Morris, Harry
d7b9d1e5-e105-40a3-9f5d-7c3e4531b32c
Morrone, Rosalinda
6d8f9343-e126-4cba-b5af-5b76664c91ce
Sinclair, Morven
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Williams, Owen
83e2f0cc-b4fa-4366-abef-7f9968febad3
Hunt, Merryn
3d2b8b80-82e4-4cb4-a8b3-30a1dd8c441d
Bandopadhyay, Subhajit
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Guo, Xuerui
c44a6885-0173-4475-a2a8-6286273524c8
Akcay, Haydar
5b918de1-4c43-4fc2-8eda-1bac58e86cf3
Dash, Jadunandan
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Brown, Luke A., Morris, Harry, Morrone, Rosalinda, Sinclair, Morven, Williams, Owen, Hunt, Merryn, Bandopadhyay, Subhajit, Guo, Xuerui, Akcay, Haydar and Dash, Jadunandan (2024) Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions. Ecological Informatics, 79, [102441]. (doi:10.1016/j.ecoinf.2023.102441).

Record type: Article

Abstract

Indirect optical measurement techniques enable efficient and non-destructive estimation of plant area index (PAI). However, because they cannot distinguish between foliage and other canopy elements, corrections are needed to determine leaf area index (LAI), which is typically the property of interest. In this study, we investigate near-infrared digital hemispherical photography (DHP) as a means of estimating and correcting for woody material. Using data collected at a deciduous broadleaf forest site, we show that near-infrared DHP could successfully estimate effective wood area index (WAIe) and wood area index (WAI) during leaf-on conditions, providing similar mean values (WAIe = 0.88, WAI = 1.53) to those determined from visible DHP during leaf-off conditions (WAIe = 0.87, WAI = 1.38). This information was used to correct estimates of effective PAI (PAIe) and PAI, enabling effective LAI (LAIe) and LAI to be derived with low RMSD (0.33 for LAIe and 0.76 for LAI), NRMSD (12% for LAIe and 19% for LAI), and bias (−0.01 for LAIe and −0.16 for LAI). Not correcting for woody material led to overestimation of LAIe by 31% on average and 46% in the worst observed case, and the degree of overestimation was further enlarged for LAI (42% on average and 61% in the worst observed case). In agreement with previous studies, the effects of clumping and woody area were found to be partly compensatory. On average, PAIe provided a reasonable approximation of LAI without correction, though overestimation of 52% and underestimation of 20% occurred at the lowest and highest LAI values, respectively. Compared to WAIe and WAI measurement using leaf-off visible DHP, near-infrared DHP offers two crucial advantages: i) data collection can be conducted at the same time as leaf-on PAIe and PAI measurements, and ii) it is likely that the approach could provide an indirect WAIe and WAI measurement option for evergreen species.

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Accepted/In Press date: 17 December 2023
e-pub ahead of print date: 22 December 2023
Published date: 2 January 2024
Keywords: DHP, Leaf area index (LAI), Near-infrared imagery, PAI, Wood area index (WAI)

Identifiers

Local EPrints ID: 503205
URI: http://eprints.soton.ac.uk/id/eprint/503205
ISSN: 1574-9541
PURE UUID: 25e0e427-36b8-4cf3-b192-ea98159b5730
ORCID for Luke A. Brown: ORCID iD orcid.org/0000-0003-4807-9056
ORCID for Subhajit Bandopadhyay: ORCID iD orcid.org/0000-0002-8657-3488
ORCID for Jadunandan Dash: ORCID iD orcid.org/0000-0002-5444-2109

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Date deposited: 24 Jul 2025 16:33
Last modified: 17 Sep 2025 01:40

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Contributors

Author: Luke A. Brown ORCID iD
Author: Harry Morris
Author: Rosalinda Morrone
Author: Morven Sinclair
Author: Owen Williams
Author: Merryn Hunt
Author: Xuerui Guo
Author: Haydar Akcay
Author: Jadunandan Dash ORCID iD

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