A new look at top-of-canopy gap fraction measurements from high-resolution airborne imagery.

Abstract

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 21 st , 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 10 th and 20 th , 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.

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