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ARS Home » Southeast Area » Tifton, Georgia » Southeast Watershed Research » Research » Publications at this Location » Publication #204863
Title: Estimating Crop Residue Distribution Using Airborne and Satellite Remote Sensing

Author
item Sullivan, Dana
item Strickland, Timothy - Tim
item MASTERS, M - FLINT WATER POL & PLAN
item YAO, H - ITD

Submitted to: Journal of Soil and Water Conservation Society
Publication Type: Abstract Only
Publication Acceptance Date: 6/30/2007
Publication Date: 7/21/2007
Citation: Sullivan, D.G., Strickland, T.C., Masters, M., Yao, H. 2007. Estimating Crop Residue Distribution Using Airborne and Satellite Remote Sensing [abstract]. Journal of Soil and Water Conservation Society Conference, Tampa, Florida 07/21/2007.

Interpretive Summary: Crop residue management and reduced tillage are commonly accepted best management practices that improve soil quality through the sequestration of soil organic carbon. A major goal of this study was to evaluate remote sensing data for rapid quantification of conservation tillage at the field and watershed scale. During 2005 and 2006, crop residue cover distribution was measured on four experimental farm sites located within the Southern Coastal Plain. Sites consisted of two conventional tilled fields and two strip tilled fields. Remotely sensed data were collected subsequent to planting using the aircraft mounted Airborne Data Multi-Spectral Imaging System (2005) and the QuickBird Satellite (2006). Remotely sensed data were acquired in the blue (470nm), green (560nm), red (660nm) and NIR (870nm) regions of the light spectrum at 1-4 meter spatial resolution. Coincident with remotely sensed data acquisition, soil and residue were grid sampled (0.20 hectares) for SOC, soil moisture content (0-2.5 cm), particle size distribution, and crop residue amount. Samples were collected within a 2 meter radius of each grid point. Ground truth data were used to evaluate the impact of change in surface conditions on our ability to remotely quantify residue cover. Data will be used to determine the most effective spatial and spectral resolution necessary to accurately assess crop residue cover and tillage regime at the field and watershed scales. Accurate and rapid estimates of cover at this scale may decrease uncertainties in watershed models currently being used to evaluate the impact of land use/management on water quality and quantity.

Technical Abstract: Crop residue management and reduced tillage are commonly accepted best management practices that improve soil quality through the sequestration of soil organic carbon. A major goal of this study was to evaluate remote sensing data for rapid quantification of conservation tillage at the field and watershed scale. During 2005 and 2006, crop residue cover distribution was measured on four experimental farm sites located within the Southern Coastal Plain. Sites consisted of two conventional tilled fields and two strip tilled fields. Remotely sensed data were collected subsequent to planting using the aircraft mounted Airborne Data Multi-Spectral Imaging System (2005) and the QuickBird Satellite (2006). Remotely sensed data were acquired in the blue (470nm), green (560nm), red (660nm) and NIR (870nm) regions of the light spectrum at 1-4 meter spatial resolution. Coincident with remotely sensed data acquisition, soil and residue were grid sampled (0.20 hectares) for SOC, soil moisture content (0-2.5 cm), particle size distribution, and crop residue amount. Samples were collected within a 2 meter radius of each grid point. Ground truth data were used to evaluate the impact of change in surface conditions on our ability to remotely quantify residue cover. Data will be used to determine the most effective spatial and spectral resolution necessary to accurately assess crop residue cover and tillage regime at the field and watershed scales. Accurate and rapid estimates of cover at this scale may decrease uncertainties in watershed models currently being used to evaluate the impact of land use/management on water quality and quantity.