Retrieving leaf area index from multi-angular airborne data

This work is aimed to demonstrate the feasibility of a methodology for retrieving bio-geophysical variables
whilst at the same time fully accounting for additional information on directional anisotropy. A model-based approach
has been developed to deconvolve the angular reflectance into single landcovers reflectances, attempting
to solve the inconsistencies of 1D models and linear mixture approaches. The model combines the geometric optics
of large scale canopy structure with principles of radiative transfer for volume scattering within individual
crowns. The reliability of the model approach to retrieve LAI has been demonstrated using data from DAISEX-
99 campaign at Barrax, Spain. Airborne data include POLDER and HyMap data in which various field plots
were observed under varying viewing/illumination angles. Nearly simultaneously, a comprehensive field data set
was acquired on specific crop plots. The inversions provided accurate LAI values, revealing the model potential
to combine spectral and directional information to increase the likely accuracy of the retrievals. In addition, the
sensitivity of retrievals with the angular and spectral subset of observations was analysed, showing a high consistency
between results. This study has contributed to assess the uncertainties with products derived from satellite
data like SEVIRI/MSG.

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