A new look at top-of-canopy gap fraction measurements from high-resolution airborne imagery|
Alemu Gonsamo and Petri Pellikka
This study is aimed
at demonstrating the feasibility of a large-scale leaf area index (LAI)
inversion using high resolution
airborne imagery without calibrating using ground based measurements. The study
area is located in the Gatineau Park, Southern Quebec, Canada.
The developed methods are evaluated in relatively high forest cover where
remote sensing retrieval of biophysical parameters is commonly ill-posed.
The airborne images were acquired on the cloud
free day of August 21st, 2007 with 35 cm and 60 cm nominal pixel
size of colour and colour infrared (CIR),
respectively in digital format. The ground LAI
measurements were collected from 54 plots of 20 m by 20 m using
hemispherical photography between August 10th and 20th,
2007 and used as an evaluation dataset. LAI and other canopy structure
parameters were computed from airborne imagery based on the principles commonly used for
the ground based optical LAI estimation.
A clumping index calculation algorithm is demonstrated using logarithmic gap
fraction averaging technique based on the gap fraction data obtained from
airborne imagery. The proposed methodology produced satisfactory results as
related to the objective. The LAI inverted from CIR imagery (Pearson
correlation coefficient with measured value R
= 0.67) outperformed that of colour imagery. In view of that, such a
methodology developed in this study could well be applicable particularly in
low forest density areas and could further be improved.