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 MATLAB 7.4 (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; R² = 0.90) and at the forest scale, MODIS LAI compared well with LAI_D (MODIS LAI = 0.9591 LAI_D – 0.2371; R² = 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; 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.