Grassland is a major component of the Earth's available land. The vast area and remoteness of this ecosystem makes it difficult to assess its condition and monitor productivity by traditional methods. Remote sensing potentially offers a rapid nondestructive approach for monitoring such ecosystems. A study was carried out in a tallgrass prairie site near Manhattan, Kansas, during the 1983 and 1984 seasons to investigate the feasibility of estimating light interception and green leaf area index (LAI) from measurements of canopy multispectral reflectance. Greenness (Gn) index was found to be strongly correlated with intercepted photosynthetically active radiation (PAR). Two methods, a direct regression (RGR) and an indirect approach (IND), were used to estimate LAI form Gn index. The LAI values estimated by RGR method were consistently lower than the measured ones; however, good agreement was obtained between the LAI values estimated by IND method and the measured LAI. This suggests that Gn transformation of canopy spectral reflectance is more closely related to the fraction of intercepted PAR by green foliage than the quantity of green LAI