An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI

Fuentes, S; Palmer, AR; Taylor, D; Zeppel, M; Whitley, R; Eamus, D

An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI

Fuentes, S Palmer, AR

Taylor, D Zeppel, M

Whitley, R Eamus, D

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Publication Type:: Journal Article
Citation:: Functional Plant Biology, 2008, 35 (10), pp. 1070 - 1079
Issue Date:: 2008-11-18

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Field	Value	Language
dc.contributor.author	Fuentes, S	en_US
dc.contributor.author	Palmer, AR https://orcid.org/0000-0001-9179-2725	en_US
dc.contributor.author	Taylor, D	en_US
dc.contributor.author	Zeppel, M https://orcid.org/0000-0002-5510-0936	en_US
dc.contributor.author	Whitley, R	en_US
dc.contributor.author	Eamus, D https://orcid.org/0000-0003-2765-8040	en_US
dc.date.issued	2008-11-18	en_US
dc.identifier.citation	Functional Plant Biology, 2008, 35 (10), pp. 1070 - 1079	en_US
dc.identifier.issn	1445-4408	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8672
dc.description.abstract	Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional-structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAI M (LAIM=1.009 - 0.0066 LAID; R 2=0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI=0.9591 LAID - 0.2371; R2=0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI=1.0296 LAIe+0.3468; R 2=0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers. © CSIRO 2008.	en_US
dc.relation.ispartof	Functional Plant Biology	en_US
dc.relation.isbasedon	10.1071/FP08045	en_US
dc.subject.classification	Plant Biology & Botany	en_US
dc.title	An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	35	en_US
utslib.for	0607 Plant Biology	en_US
utslib.for	0601 Biochemistry and Cell Biology	en_US
utslib.for	0602 Ecology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access
pubs.issue	10	en_US
pubs.publication-status	Published	en_US
pubs.volume	35	en_US

Abstract:

Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional-structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAI M (LAIM=1.009 - 0.0066 LAID; R 2=0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI=0.9591 LAID - 0.2371; R2=0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI=1.0296 LAIe+0.3468; R 2=0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers. © CSIRO 2008.

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