Optical–Biophysical Relationships of Vegetation Spectra without Background Contamination

For a better evaluation of the accuracy of VIs in estimating biophysical parameters, a “true” VI value attributed only to the vegetation signal and free of any contamination is needed. In this article, pure vegetation spectra were extracted from a set of open and closed canopies by unmixing the green vegetation signal from the background component. Canopy model-simulation and reflectances derived from graph-based linear extrapolation were used to unmix and derive a “true” vegetation signal, equivalent to a perfect absorber (free boundary) canopy background reflectance condition. Optical–biophysical relationships were then derived for a variety of canopy structures with differences in foliage clumping, horizontal heterogeneity, and leaf type. A 3-dimensional canopy radiative transfer model and a hybrid geometric optical-radiative transfer model (GORT) were used to simulate the directional-hemispherical reflectances from agricultural, grassland, and forested canopies (cereal and broadleaf crop, grass, needleleaf, and broadleaf forest). The relationships of the extracted red and near-infrared reflectances and derived vegetation indices (VIs) to various biophysical parameters (leaf area index, fraction of absorbed photosynthetically active radiation, and percent ground cover) were examined for the pure vegetation spectra. The results showed normalized difference vegetation index (NDVI) relationships with biophysical parameters to become more asymptotic over the pure vegetation condition. The extraction of pure vegetation signals had little effect on the soil-adjusted vegetation index (SAVI), which had values equivalent to those obtained with the presence of a background signal. NDVI values were fairly uniform across the different canopy types, whereas the SAVI values had pronounced differences among canopy types, particularly between the broadleaf and cereal/needleleaf structural types. These results were useful not only in selecting suitable vegetation indices to characterize specific canopy biophysical parameters, but also in understanding a “true” VI behavior, free of background noise.