Abstract
The remote sensing of agricultural crops has concentrated on the use of red and near-infrared radiance. The increasing availability of middle and thermal infrared radiance data has opened up a new source of spectral information. In grassland areas middle and thermal infrared radiance are usually negatively related to green leaf area index (GLAI). These data can be used in vegetation indices (in addition to red and near-infrared radiance data) to model the GLAI-radiance relationship empirically. The accuracy of GLAI estimation was significantly increased using such indices rather than a red/near-infrared based index. These increases were masked when applying a methodology to allow for sampling error and it is suggested that this was due to this section of the methodology rather than insufficient spectral information from the middle and thermal infrared wavebands.