Estimating Canopy Height of Montane Cool Temperate Forest Using Large-footprint Spaceborne Lidar

Estimation of forest carbon storage is a critical challenge for understanding the global carbon cycle because it dominates the dynamics of the terrestrial carbon cycle. Light Detection and Ranging (LiDAR) system has a unique capability for estimating accurately forest canopy height, which has a direct relationship and can provide better understood to the aboveground carbon storage. To test the capacity of the large-footprint LiDAR for estimating canopy height in the montane cool temperate forest, the full waveform data of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) was used to extract forest canopy height in Wangqing of China. In this study, the maximum forest canopy height was regressed as a function of waveform extent and the elevation change in terms of terrain slope ranges. Final regression model for slope range of 0 to <5° explained 81% variance of maximum canopy height. With the increasing of slope ranges, the model accuracies significantly declined. The regression model could explain 61% and 47% of variance at the plots of which the terrain slope within 0 to <10° and 0 to <15° respectively. When the terrain slope is beyond 16°, the regression models became not so reliable anymore with less than 36% agreement. The results showed that the GLAS waveform data provides reasonable prediction for the maximum canopy height in the cool temperate forest of Northeast China.