Remote estimation of leaf area index in forested ecosystems

Leaf area index (LAI) is defined as the ratio of the foliage area contained within a given area divided by the ground area in question.; Remote sensing models have traditionally attempted to use spectral vegetation indices to model variations in LAI. However, these models have achieved only moderate success because their accuracy is often dependent on the influence of the background. Recently, two promising techniques have been applied for remote LAI estimation: linear spectral mixture analysis and modification of spectral vegetation indices. These techniques offer explicit strategies for the mitigation of background effects. Additional remote estimation techniques have been developed specifically for this study, namely the scale factor and the normalized distance methods.; These remote estimation models are derived and compared for a region of montane forest in Kananaskis Country.; The results of this study indicate that the best overall technique for remote LAI estimation is the normalized distance method. The other modeling techniques exhibit varying degrees of modeling success, while evincing significant dependence on vegetation type. (Abstract shortened by UMI.)...