Applicability of the PROSPECT model for estimating protein and cellulose + lignin in fresh leaves

摘要: Abstract Hyperspectral remote sensing of leaf biochemicals is critical for understanding many biochemical processes. Leaf contents (e.g., protein, cellulose and lignin) in fresh dry leaves have been quantified from hyperspectral data using empirical models. However, they cannot be retrieved by inverting radiative transfer We demonstrated the applicability PROSPECT optical properties model separation specific absorption coefficients protein cellulose + lignin following a newly proposed algorithm, evaluated feasibility estimating content through inversion. Assessment was performed across large variety plant species benefiting Optical Properties Experiment (LOPEX) dataset. To alleviate ill-posed problems, inversion over different spectral subsets. The with calibrated able to accurately reconstruct reflectance transmittance. were estimated at moderate good accuracies both leaves. subset 2100–2300 nm yielded most accurate estimation ( R 2  = 0.70, RMSE = 5.21E − 04 g/cm )  = 0.47, RMSE = 2.75E − 04 g/cm leaves, which comparable those obtained stepwise multiple linear regressions (protein:  = 0.83, RMSE = 3.91E − 04 g/cm ; cellulose + lignin:  = 0.66, RMSE = 2.02E − 04 g/cm ). Our results confirm importance selecting proper that contains sufficient information successful For first time, we provide promising estimations model, can applied canopy level regional mapping if coupled air- or space-borne imaging.