Estimating semiarid vegetation height from GLAS Data

The Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud and land Elevation Satellite (ICESat), operational from 2003-2009, was the first space-borne light detection and ranging (LiDAR) system capable of providing full waveform large-footprint LiDAR data at a near-global scale. GLAS was designed primarily for ice information measurement, but has been widely used to characterize vegetation structure and estimate canopy heights and biomass over a range of forest types and topography. GLAS data, however, have not been used to estimate semiarid vegetation, with typically low height stature. We investigate the ability of GLAS data to estimate vegetation height and density at the Idaho National Laboratory (INL) in southeastern Idaho, an area of very low topographic relief, minimizing within-footprint topographic and vegetation variation. Vegetation derivatives obtained from GLAS data are compared to airborne LiDAR data collected over the same area in 2006 for uncertainty estimates. Accurate vegetation canopy characterization with GLAS will provide large-scale biomass estimates, along with roughness estimates for surface energy balance models and weather forecasting.