Evaluation of Multispectral Data for Rapid Assessment of Wheat Straw Residue Cover

share programs, such as the Environmental Quality Incentives Program (EQIP). According to the 1985 Food Crop residues influence near surface soil organic carbon (SOC) Security Act, lands considered ‘highly erodible’ must content, impact our ability to remotely assess soil properties, and play a role in global carbon budgets. Methods that measure crop residues implement an acceptable conservation program to reare laborious, and largely inappropriate for field-scale to regional main eligible for farm benefits. Furthermore, cost-share estimates. The objective of this study was to evaluate high spectral recipients for reduced tillage systems must maintain a resolution remote sensing (RS) data for rapid quantification of residue minimum of 30 to 50% crop residue cover to receive procover. In March 2000 and April 2001, residue plots (15 by 15 m) were gram reimbursements. Current line-transect techniques established in the Coastal Plain and Appalachian Plateau physioare labor intensive and accuracy is often a function of graphic regions of Alabama. Treatments consisted of five wheat (Tritiline length and the number of data points collected. cum aestivum L.) straw cover rates (0, 10, 20, 50, and 80%) replicated Remote sensing techniques using high spatial and specthree times. Spectral measurements were acquired monthly via a handtral resolution sensors may facilitate field-scale and reheld spectroradiometer (350–1050 nm) and per availability via the gional crop residue cover assessment. Airborne Terrestrial Applications Sensor (ATLAS) (400–12 500 nm). Overall, treatment separation was influenced by soil water content Unlike growing vegetation, there is a general lack and percentage of total organic carbon (TOC) of the residue (degree of information regarding spectral signatures associated of decomposition). Results showed that atmospherically corrected with decaying crop residues. However, a fundamental visible and near-infrared ATLAS data can differentiate between resiunderstanding of molecular functional groups in growdue coverages. Similar results were obtained with the handheld specing and senescent vegetation provides a foundation for troradiometer, although treatment differentiation was less consistent. addressing residue spectra. Functional groups present in Thermal infrared ATLAS imagery best discriminated among residue plant material, such as CH3, OH, and H2O, significantly treatments due to differing heat capacities between soil and residue. affect spectral response properties via the presence of abResults from our study suggest airborne thermal infrared (TIR) imagsorption bands within the 700to 2600-nm range (Murray ery can be used for crop residue variability assessment within the and Williams, 1988). During the initial stages of tissue southeastern USA. chlorophyll loss, spectral response is greatest from 400 to 800 nm, as senescent plant tissues absorb incoming blue (300–400 nm) and red (500–600 nm) spectra while A of minimum tillage with residue managereflecting green (400–500 nm). Presence of water at this ment strategies has been widely associated with stage masks absorbance features in the near infrared improvements to soil quality. Crop residue management (NIR) associated with lignin and cellulose (Elvidge, 1990). enhances soil quality primarily through the accumulaAs decay progresses, the relative abundance of lignin tion of SOC. Benefits attributable to residue manageand cellulose present is evidenced by broad absorption ment include reduced erosion, improved infiltration, and bands throughout the 400to 900-nm spectral region soil aggregation (Prasad and Power, 1991). Since 33% (Elvidge, 1990). of agricultural lands in the USA have been classified Studies conflict regarding the use of remote sensing as highly erodible, residue management can effectively data to reliably differentiate between residue and soil. reduce erosion and off-site transport of nutrients and Early attempts to differentiate between soil and residue pesticides (USDA, 1995; McMurtrey et al., 1993; Lal spectra showed differences in spectral reflectance were and Kimble, 1997). A rapid method of monitoring fieldgreatest in the NIR (Gausman et al., 1973; Aase and scale distribution of residue cover could help better Tanaka, 1991). These results are in congruence with a establish the benefits of conservation tillage to soil and similar study conducted by McMurtrey et al. (1993). water quality. McMurtrey et al. (1993) developed a vegetation index Problems with field-scale residue coverage assessments using spectrophotometer data of five different crop resiarise because obtaining spatially representative estimates dues and four different soil types. McMurtrey et al. of residue cover in a timely and cost efficient manner (1993) found reflection at 450, 660, and 830 nm captured is difficult. Cover estimates are increasingly important most differences between soil and crop residue spectra due to eligibility and compliance with government costin a laboratory setting. In another study, Daughtry et al. (1995) utilized reflectance data to distinguish between D.G. Sullivan, USDA-ARS Southeast Watershed Research Laboraa variety of crop residues and soils representing 14 subtory, Tifton, GA 31794; J.N. Shaw, P.L. Mask, and E.A. Guertal, Dep. orders. Results showed visible (VIS) and NIR energy of Agronomy and Soils, Auburn University, Auburn, AL 36849; D. Rickman and J. Luvall, Global Hydrology and Climate Center, Huntscould not reliably distinguish soil from residue due to ville, AL 35805; J.M. Wersinger, Physics Dep., Auburn University variability in soil properties, water content, and residue Auburn, AL 36849. Received 25 May 2004. *Corresponding author ([email protected]). Abbreviations: ATLAS, Airborne Terrestrial Applications Sensor; CAI, cellulose absorption index; CV, coefficient of variation; NIR, Published in Soil Sci. Soc. Am. J. 68:2007–2013 (2004).  Soil Science Society of America near infrared; RS, remote sensing; SOC, Soil organic carbon; TC, total carbon; TIR, thermal infrared; TOC, total organic carbon; VIS, visible. 677 S. Segoe Rd., Madison, WI 53711 USA