Evaluation of waveform deconvolution and decomposition retrieval algorithms for ICESat/GLAS data

The Ice, Cloud and Land Elevation Satellite (ICESat) with the Geoscience Laser Altimeter System (GLAS) data provides a new potential for extracting information on the vertical structure of vegetation worldwide. Analysis of the returned full-waveform energy over areas of low topography allows for the direct retrieval of canopy heights. The returned laser energy is a complex interaction between surface scattering and the outgoing laser properties. In addition, the return pulse is convolved with the outgoing system response. Laser ranges are determined by computing the laser travel time between the outgoing pulse and the return pulse. This research examines deconvolution and Gaussian decomposition as a methodology for locating ranging locations on the return pulse. Heights retrieved from ICESat/ GLAS using both deconvolution and Gaussian decomposition were evaluated against heights derived from a small-footprint, full-waveform dataset. Early results indicate that ranges derived from deconvolution revealed vertical elements within the ICESat footprint better than the Gaussian decomposition, including understory vegetation at a height similar to 1.5 m above the ground surface. The utilization of deconvolution prior to waveform analysis was found to improve ground estimates and detect additional information about the canopy structure.