Effective LAI and CHP of a Single Tree From Small-Footprint Full-Waveform LiDAR

Karolina D. Fieber, Ian J. Davenport, Mihai A. Tanase, James M. Ferryman, Robert J. Gurney, Jeffrey P. Walker, Jorg M. Hacker
2014 IEEE Geoscience and Remote Sensing Letters  
This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index (LAI 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 LAI e of a single live Callitris glaucophylla tree. LAI e was extracted from raw waveform as an intermediate step in the CHP methodology, with two different vegetation-ground reflectance
more » ... -ground reflectance ratios. Discrete point LAI e estimates were derived from the gap probability using the following: 1) single ground returns and 2) all ground returns. LiDAR LAI e retrievals were subsequently compared to hemispherical photography estimates, yielding mean values within ±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 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. Index Terms-Canopy height profile (CHP), effective leaf area index (LAI e ), full-waveform airborne LiDAR, single tree, Soil Moisture Active Passive Experiment (SMAPEx), vegetation profile.
doi:10.1109/lgrs.2014.2303500 fatcat:sf7bvnchyrdnnauuzvggb5qbk4