/AnMtgsAbsts2009.51695 Mapping Crop Residue Cover at Field to Regional Scales.

Monday, November 2, 2009: 11:50 AM
Convention Center, Room 336, Third Floor

Craig Daughtry1, Paul Doraiswamy1, E. Raymond Hunt1, Guy Serbin2, Jerry Hatfield3, M. M Crawford4 and Tony Vyn5, (1)USDA-ARS, Hydrology & Remote Sensing Lab., Beltsville, MD
(2)ASRC Management Services, Washington, DC
(3)USDA-ARS, Natl. Soil Tilth Lab., Ames, IA
(4)Laboratory for Applications of Remote Sensing, Purdue Univ., West Lafayette, IN
(5)Purdue Univ., West Lafayette, IN
Abstract:
Management of crop residues in agricultural fields is an important consideration for reducing soil erosion and increasing soil organic C. Current methods of quantifying crop residue cover are inadequate for characterizing the spatial variability of residue cover within fields or across large regions. Our objectives were to evaluate spectral indices for measuring crop residue cover and to categorize soil tillage intensity in agricultural fields. Ground-, aircraft- and satellite-based multispectral and hyperspectral data were acquired over corn (Zea mays L.) and soybean (Glycine max Merr.) fields in Iowa, Indiana, and Maryland in the Spring, shortly after most fields in the area were planted. Crop residue cover was measured in using line-point transects. Crop residue cover was weakly related to the spectral residue indices that used the relatively broad Landsat TM bands. However, spectral residue indices that measured the relatively narrow spectral absorption features associated with cellulose and lignin near 2100 or 2350 nm were robust and were often linearly related to crop residue cover.  Tillage intensity classes, based on residue cover after planting, were combined with information on the previous season’s crop classification (Cropland Data Layer from USDA-NASS) to produce an inventory of soil tillage intensity for each scene.  Regional surveys of soil management practices that affect soil conservation and soil C dynamics are possible using advanced multispectral or hyperspectral imaging systems.