Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 30, 2003
Publication Date: January 2, 2004
Citation: Daughtry, C.S., Hunt, E.R., McMurtrey, J.E. 2004. Assessing crop residue cover by remote sensing. Remote Sensing of Environment. 90:126-134. Interpretive Summary: Management of crop residues is a major consideration in many conservation tillage practices. Crop residues decrease water and wind erosion of soils and increase soil quality. By reducing the movement of eroded soil into streams and rivers, the movement of nutrients and pesticides is reduced. The overall result is less soil erosion and improved water quality. The standard technique for measuring crop residue cover used by the USDA Natural Resources Conservation Service (NRCS) is visual estimation along a line-transect. Rapid, accurate, and objective methods to quantify residue cover in individual fields are needed for management decisions. We analyzed the reflectance of soils and crop residues and identified a n absorption feature in the spectral of the crop residues that was absent in the spectra of the soils. We developed a simple 3-band index that was related to the percent of residue cover. This reflectance technique appears promising for field and regional surveys of crop residue cover and tillage practices.
Technical Abstract: Management of crop residues is an important consideration for reducing soil erosion and increasing soil organic carbon. Current methods of measuring residue cover are inadequate in characterizing the spatial variability of residue cover over large fields. The objectives of this research were to determine the spectral reflectance of crop residues and soils, to evaluate the theoretical limits of discrimination that can be expected, and to evaluate the approach in field conditions. Spectral reflectances of corn and soybean residues plus three diverse soils were measured over the 400-2400 nm wavelength region at a wide range of moisture conditions in the laboratory. Additional spectra of scenes with mixtures of crop residues, green vegetation, and soil were also acquired in production fields. Reflectance factors for scenes varying proportions of crop residues and soils were simulated. The spectra of dry crop residues displayed a broad absorption feature near 2100 nm, associated with lignin-cellulose, that was absent in spectra of soils. The relative depth of the lignin-cellulose absorption feature, defined as Cellulose Absorption Index (CAI), was positively correlated to the fraction of residue cover. The wide range of CAI values expected for dry and moist conditions makes quantification of crop residue cover feasible. Regional surveys and maps of crop residue cover and tillage practices appears to be feasible using hyperspectral imaging systems.