Estimation of forest canopy height and above-ground biomass using ICESat full waveform data: a case study in Changbai Mountain, China

Abstract

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 understanding to the aboveground carbon storage. This study aimed to test the capacity of large-footprint full waveform LiDAR for estimating forest canopy height and aboveground biomass in the cool temperate forest over sloped terrain. The full waveform data of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) was used to achieve the aim in Wangqing of Changbai Mountain. The maximum canopy height was first regressed as a function of waveform extent and the elevation change for evaluating the Lefsky's model. Then an improved model of maximum forest canopy height against the logarithm of waveform extent and the elevation change was tested for improving the accuracy of forest canopy height estimation. Finally the aboveground forest biomass was related to ICESat-derived maximum canpy height from the improved model. The results showed that the Lefsky's model and the improved model explained 51% and 74% of variation of maximum canopy height for the terrain slope range of 0~15°, respectively, and the improved model performed better than the Lefsky's model for estimating forest maximum canopy height over the sloped terrain. The ICESat-derived maximum canpy height from the improved model explained 52% of variation of the aboveground forest biomass. The results indicated that the ICESat-GLAS full waveforms are promising for estimating maximum forest canopy height and aboveground biomass in the study area.