Leaf pigment retrieval using the PROSAIL model: Influence of uncertainty in prior canopy-structure information

Leaf pigments are critical indicators of plant photosynthesis, stress, and physiological conditions. Inversion of radiative transfer models (RTMs) is a promising method for robustly retrieving leaf biochemical traits from canopy observations, and adding prior information has been effective in alleviating the “ill-posed” problem, a major challenge in model inversion. Canopy structure parameters, such as leaf area index (LAI) and average leaf inclination angle (ALA), can serve as prior information for leaf pigment retrieval. Using canopy spectra simulated from the PROSAIL model, we estimated the effects of uncertainty in LAI and ALA used as prior information for lookup table-based inversions of leaf chlorophyll (C_ab) and carotenoid (C_ar). The retrieval accuracies of the two pigments were increased by use of the priors of LAI (RMSE of C_ab from 7.67 to 6.32 μg cm⁻², C_ar from 2.41 to 2.28 μg cm⁻²) and ALA (RMSE of C_ab from 7.67 to 5.72 μg cm⁻², C_ar from 2.41 to 2.23 μg cm⁻²). However, this improvement deteriorated with an increase of additive and multiplicative uncertainties, and when 40% and 20% noise was added to LAI and ALA respectively, these priors ceased to increase retrieval accuracy. Validation using an experimental winter wheat dataset also showed that compared with C_ar, the estimation accuracy of C_ab increased more or deteriorated less with uncertainty in prior canopy structure. This study demonstrates possible limitations of using prior information in RTM inversions for retrieval of leaf biochemistry, when large uncertainties are present.