Exploiting multisensor spectral data to improve crop residue cover estimates for management of agricultural water quality

Crop residue is an important factor in determining soil structure relative to soil organic matter content, water infiltration, evaporation, and soil temperature [1]. There is also a direct impact related to production of biofuels. The use of the NDTI (Normalized Difference Tillage Index [2]) from multispectral data and the CAI (Cellulose Absorption Index [3]) from hyperspectral data are investigated as a means of calibrating indices derived from the Advanced Land Imager (ALI) on the EO-1 satellite and Landsat TM, with the goal of improving residue cover estimates over extended areas.