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Plant function and evolutionary biology
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RESEARCH ARTICLE
Contents Vol 35(10)

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

Sigfredo Fuentes A B C , Anthony R. Palmer B , Daniel Taylor B , Melanie Zeppel B , Rhys Whitley B and Derek Eamus B
+ Author Affiliations
- Author Affiliations

A Plant Research Centre, University of Adelaide, Waite Campus, PMB 1 Glen Osmond, SA 5064, Australia.

B Institute for Water and Environmental Resource Management (IWERM), University of Technology, Sydney, NSW 2007, Australia.

C Corresponding author. Email: sigfredo.fuentes@adelaide.edu.au

This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Functional Plant Biology 35(10) 1070-1079 https://doi.org/10.1071/FP08045
Submitted: 5 March 2008  Accepted: 25 September 2008   Published: 11 November 2008

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 LAIM (LAIM = 1.009 – 0.0066 LAID; R2 = 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; R2 = 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.

Additional keywords: digital imagery, Eucalyptus, leaf area index, MATLAB, MODIS LAI, remote sensing.


Acknowledgements

We thank Chris Hunt from Agresearch, Grasslands in New Zealand for his technical support.


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