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.

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Journal Article
Functional Plant Biology, 2008, 35 (9-10), pp. 1070 - 1079
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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 (LAI(D)) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAI(D) (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 MATLAB7.4 (LAI(M)). Furthermore, we used this method to compare MODIS LAI values with LAI(D) 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 LAI(M). Good relationships were achieved when comparing averaged LAI(D) and LAI(M) (LAI(M) = 1.009-0.0066 LAI(D); R(2) = 0.90) and at the forest scale, MODIS LAI compared well with LAI(D) (MODIS LAI = 0.9591 LAI(D)-0.2371; R(2) = 0.89). This comparison improved when correcting LAI(D) with the clumping index to obtain effective LAI (MODIS LAI = 1.0296 LAI(e) + 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.
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