부산대학교 도서관

This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index $(\hbox{LAI}_{\rm e})$ and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from six swaths, as well as from the combined data of six swaths, were used to extract the $\hbox{LAI}_{\rm e}$ of a single live Callitris glaucophylla tree. $\hbox{LAI}_{\rm e}$ was extracted from raw waveform as an intermediate step in the CHP methodology, with two different vegetation-ground reflectance ratios. Discrete point $\hbox{LAI}_{\rm e}$ estimates were derived from the gap probability using the following: 1) single ground returns and 2) all ground returns. LiDAR $\hbox{LAI}_{\rm e}$ retrievals were subsequently compared to hemispherical photography estimates, yielding mean values within $\pm$7% of the latter, depending on the method used. The CHP of a single dead Callitris glaucophylla tree, representing the distribution of vegetation material, was verified with a field profile manually reconstructed from convergent photographs taken with a fixed-focal-length camera. A binwise comparison of the two profiles showed very high correlation between the data reaching ${\rm R}^{2}$ of 0.86 for the CHP from combined swaths. Using a study-area-adjusted reflectance ratio improved the correlation between the profiles, but only marginally in comparison to using an arbitrary ratio of 0.5 for the laser wavelength of 1550 nm.