Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/20/2000
Publication Date: N/A
Citation: Interpretive Summary: Over one-third of tilled U.S. cropland is classified as highly erodible land. Crop residue on the soil surface reduces soil erosion. Crop residue management can be an important factor in controlling soil erosion. By reducing the movement of eroded soil into streams and rivers, the movement of nutrients and pesticides attached to soil particles is also reduced. The overall result is less soil erosion and improved water quality. Current methods for quantifying crop residue cover are tedious and somewhat subjective. Our overall objective was to develop new methods to measure crop residue cover that are rapid, accurate, and objective. In this paper, we evaluated the feasibility of using remotely sensed data to discriminate intact crop residues from soils. A remotely sensed cellulose absorption index (CAI) was defined that was positive for crop residues and negative for soil. This new technique for determining crop residue cover reliably discriminates crop residues from soils under a wide range of moisture conditions in the laboratory. Additional evaluations under field conditions are planned. If the field tests are successful, this could be a new tool for the Natural Resources Conservation Service (NRCS) for measuring crop residue cover in individual fields, as well as large areas.
Technical Abstract: There is a need for new methods to quantify residue cover that are rapid, accurate, and objective. In the visible and near infrared (IR), crop residues may be brighter or darker than soils. The feasibility of using lignin-cellulose absorption features to discriminate intact crop residues from soils was evaluated as a function of water content. The spectra of dry crop residues displayed a broad absorption feature, associated with lignin-cellulose, that was absent in the spectra of soils. A spectral variable, Cellulose Absorption Index (CAI), was defined. All crop residues, except those saturated with water, have positive values of CAI while all soils have negative CAI values. Water significantly altered reflectance spectra of wet residues, but did not completely inhibit discrimination. The reflectance for mixed pixels (i.e., with varying proportions of soil and residue) was simulated and CAI was calculated for various moisture conditions. A change of one tenth in the fraction of residue cover produced significant differences in CAI for the mixtures of dry and moist crop residues and soils. However, the narrow range of CAI values for the mixtures of wet residues and soils made discrimination difficult. This new technique for determining crop residue cover appears promising, but additional work is needed to determine whether these differences are detectable under field conditions.