Preliminary leaf area index estimates from airborne small footprint full-waveform LiDAR dataFieber, K. D., Davenport, I. J., Tanase, M. A., Ferryman, J., Gurney, R. J., Walker, J. P. and Hacker, J. M. (2013) Preliminary leaf area index estimates from airborne small footprint full-waveform LiDAR data. In: Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International, 21-26 July 2013, Melbourne, VIC, pp. 3379-3382. Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Official URL: http://dx.doi.org/10.1109/IGARSS.2013.6723553 Abstract/SummaryThis study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clouds. LAI LiDAR estimates were derived in two ways (1) from the probability of discrete pulses reaching the ground without being intercepted (point method) and (2) from raw waveform canopy height profile processing adapted to small-footprint laser altimetry (waveform method) accounting for reflectance ratio between vegetation and ground. The best results, that matched hemispherical photography estimates, were achieved for the waveform method with a study area-adjusted reflectance ratio of 0.4 (RMSE of 0.15 and 0.03 at plot and site level, respectively). The point method generally overestimated, whereas the waveform method with an arbitrary reflectance ratio of 0.5 underestimated the fish-eye lens LAI estimates.
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