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