Estimating leaf biochemistry using the PROSPECT leaf optical properties model

Thc biophysical, biochemical, and optical properties of 63 fresh leaves and 58 dry leaves were measured to investigate the potential of remote sensing to estimate the leaf biochemistry from space. Almost 2000 hemispherical reflectance and transmittance spectra were acquired from 400 nm to 2500 nm using a laboratory spectrophotometer. The amount of chlorophyll, water protein, cellulose, hemicellulose, lignin, and starch was determined on these leaves using standard wet chemistry techniques. These experimental data were used to improve the PROSPECT model, a simple but effective radiative transfer model that calculates the leaf optical properties with a limited number of input parameters: a structure parameter and the leaf biochemistry. The new model construction mainly consisted in. providing specific absorption coefficients for the biochemical constituents; the comparison with absorption spectra of pure materials derived from the literature showed good agreement. In the inversion, however, it was necessary to group some leaf components in order to estimate leaf biochemistry with reasonable accuracy. Predictive power varied with the chemistry variable, wavelengths used in analysis, and whether leaves were fresh or dry. r(2) ranged from 0.39 to 0.88 for predictions on dry leaves; on fresh leaves, water and chlorophyll had high r(2) values, 0.95 and 0.68 respectively, carbon based compounds reasonable r(2), from 0.50 to 0.88, while the estimation of protein is still at issue.