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Maximum Canopy Height Estimation Using ICESat GLAS Laser Altimetry

To understand forest structures, the Geoscience Laser Altimeter System (GLAS) instrument
have been employed to measure and monitor forest canopy with feasibility of acquiring three dimensional
canopy structure information. This study tried to examine the potential of GLAS dataset in measuring forest
canopy structures, particularly maximum canopy height estimation. To estimate maximum canopy height
using feasible GLAS dataset, we simply used difference between signal start and ground peak derived from
Gaussian decomposition method. After estimation procedure, maximum canopy height was derived from
airborne Light Detection and Ranging (LiDAR) data and it was applied to evaluate the accuracy of that of
GLAS estimation. In addition, several influences, such as topographical and biophysical factors, were
analyzed and discussed to explain error sources of direct maximum canopy height estimation using GLAS
data. In the result of estimation using direct method, a root mean square error (RMSE) was estimated at
8.15 m. The estimation tended to be overestimated when comparing to derivations of airborne LiDAR.
According to the result of error occurrences analysis, we need to consider these error sources, particularly
terrain slope within GLAS footprint, and to apply statistical regression approach based on various
parameters from a Gaussian decomposition for accurate and reliable maximum canopy height estimation.
Key Words : Maximum canopy height, Geoscience Laser Altimeter System (GLAS), Airborne Light
Detection and Ranging (LiDAR), Waveform analysis