Technical Abstract: Remote sensing has facilitated extraordinary advances in modeling, mapping, and the understanding of ecosystems. Conventional sensors have significant limitations for ecological and forest applications. The sensitivity and accuracy of these devices have repeatedly been shown to fall with increasing aboveground biomass and LAI. They are also limited in their ability to represent the spatial patterns. Ecologists have long understood that the presence of specific organisms and the overall richness of wildlife communities can be highly dependent on the three-dimensional spatial pattern of vegetation. Additionally, aspects of forests, such as productivity, may be related to forest canopy structure. Lidar (light detecting and ranging) is an alternative remote sensing technology that promises to both increase the accuracy of biophysical measurements and extend spatial analysis into the third dimension (z). Multi-return Lidar sensors directly measure the three-dimensional distribution of forest canopies as well as sub-canopy topography, and therefore providing high resolution topographic maps and highly accurate estimates of tree height, cover, and canopy structure. In addition, lidar has been shown to accurately estimate LAI and aboveground biomass, even in those high biomass ecosystems, where passive optical and active radar sensors typically fail to do so. Estimation of forest structural attributes, such as LAI, is an important step in identifying the amount of water use in forest areas.