Estimation of forest height and above ground biomass from ICESat/GLAS data in Eucalyptus plantations in Brazil

The Geoscience Laser Altimeter System (GLAS) has provided a useful dataset for estimating forest height in many areas of the globe. Most of the studies on GLAS waveforms have focused on natural forests and only a few were conducted over forest plantations. The objective of this study was to test the best known models used for estimating canopy height and above ground biomass of intensively managed Eucalyptus plantations in Brazil using full waveform LiDAR data. Studies to estimate forest heights from LiDAR data have highlighted that the fitting coefficients of developed models are strongly dependent on environmental factors such as the region of the study site, terrain topography, and forest type. In this study, we evaluated the main models developed to predict canopy height using a combination of parameters extracted from GLAS waveforms and a digital elevation model, in order to explore which combination of parameters yields the best forest height estimates. In addition, a model to estimate above ground biomass from dominant height was calibrated.