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Division S-6—Soil & Water Management & Conservation

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

^a USDA-ARS Southeast Watershed Research Laboratory, Tifton, GA 31794
^b Dep. of Agronomy and Soils, Auburn University, Auburn, AL 36849
^c Global Hydrology and Climate Center, Huntsville, AL 35805
^d Physics Dep., Auburn University Auburn, AL 36849

^* Corresponding author (dgs{at}tifton.usda.gov)

Crop residues influence near surface soil organic carbon (SOC) content, impact our ability to remotely assess soil properties, and play a role in global carbon budgets. Methods that measure crop residues are laborious, and largely inappropriate for field-scale to regional estimates. The objective of this study was to evaluate high spectral resolution remote sensing (RS) data for rapid quantification of residue cover. In March 2000 and April 2001, residue plots (15 by 15 m) were established in the Coastal Plain and Appalachian Plateau physiographic regions of Alabama. Treatments consisted of five wheat (Triticum aestivum L.) straw cover rates (0, 10, 20, 50, and 80%) replicated three times. Spectral measurements were acquired monthly via a handheld spectroradiometer (350–1050 nm) and per availability via the Airborne Terrestrial Applications Sensor (ATLAS) (400–12500 nm). Overall, treatment separation was influenced by soil water content and percentage of total organic carbon (TOC) of the residue (degree of decomposition). Results showed that atmospherically corrected visible and near-infrared ATLAS data can differentiate between residue coverages. Similar results were obtained with the handheld spectroradiometer, although treatment differentiation was less consistent. Thermal infrared ATLAS imagery best discriminated among residue treatments due to differing heat capacities between soil and residue. Results from our study suggest airborne thermal infrared (TIR) imagery can be used for crop residue variability assessment within the southeastern USA.

Abbreviations: ATLAS, Airborne Terrestrial Applications Sensor • CAI, cellulose absorption index • CV, coefficient of variation • NIR, near infrared • RS, remote sensing • SOC, Soil organic carbon • TC, total carbon • TIR, thermal infrared • TOC, total organic carbon • VIS, visible

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