Broad band vegetation indices (VI) are ordinarily used to estimate biophysical parameters that can be incorporated in models to predict evapotranspiration and crop yield (Myneni et al., 1995). These indices are based on both high absorption of visible solar radiation by plant pigments and high scattering of near-infrared solar radiation by intercellular air spaces in the leaf mesophyll (Gates et al., 1965). The most widely used VI to estimate biomass, leaf area index (LAI) and absorbed photosynthetically active radiation (Asrar et al., 1984, Turner et al., 1999, Xavier & Vettorazzi, 2004) are Simple Ratio (SR; Jordan, 1969) and Normalized Difference Vegetation Index (NDVI; Rouse et al., 1974). More recently, Huete (1988) developed the Soil-Adjusted Vegetation Index (SAVI) to reduce soil background effects.
With the advancement of hyperspectral radiometers not only for laboratory or field but also for orbital measurements (e.g. Hyperion sensor on board of EO-1; Earth Observation-1, 2003), new methods to analyze spectral reflectance data were developed. For example, spectral derivative analysis of vegetation spectral reflectance measurements appear to be less sensitive to soil background reflectance effects (Demetriades-Shah et al., 1990). Elvidge & Chen (1995) and Chen et al. (1998) developed several indices from spectral derivative reflectance curves in the red-edge region (620-795 nm) due to their low sensitivity to soil background variations, when compared to broad band VI. On the other hand, Broge & Leblanc (2001) found that hyperspectral data are not better than broad band data to estimate LAI values higher than 2.8.
In the present work, wheat spectral reflectance field measurements were analyzed in terms of narrow and broad band vegetation indices to estimate final grain yield and plant height at several growth stages during crop growing season.