102630 Assessing Soil Tillage Intensity Across Watersheds.

Poster Number 462-617

See more from this Division: SSSA Division: Soil and Water Management and Conservation
See more from this Session: Soil and Water Management and Conservation Poster II

Wednesday, November 9, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Craig S. T. Daughtry, 10300 Baltimore Ave, USDA-ARS, Beltsville, MD, W. Dean Hively, USGS, Beltsville, MD, Alan Stern, Hydrology and Remote Sensing Laboratory, USDA-ARS, Beltsville, MD, Douglas L. Karlen, USDA-ARS, Ames, IA and Miguel Quemada, Dept. Agricultural Production, Technical University of Madrid, Madrid, Spain
Abstract:
Crop residues on the soil surface contribute to soil quality and form the first line defense against the erosive forces of water and wind.  After harvest, crop residues often completely cover the soil, but tillage and biofuel harvesting decrease crop residue cover.  Thus, quantifying crop residue cover on the soil surface after crops are planted is crucial for monitoring soil tillage intensity and assessing the extent of conservation practices in agricultural landscapes.  Currently, no program exists for objectively monitoring crop residue cover or tillage intensity over broad areas.  Although remote sensing could provide efficient and objective information about tillage intensity, most current multispectral satellite sensors lack appropriate spectral bands to reliably distinguish crop residues from soil. 

We evaluated broad- and narrow-band multispectral indices for estimating crop residue cover in corn and soybean fields in a watershed in central Iowa.  Tillage indices developed using the widely available Landsat multispectral data were not robust and required local calibrations to account for changes in soils, crops, and scene moisture.  However the narrow shortwave infrared bands of the Digital Globe WorldView-3 satellite sensor reliably estimated crop residue cover with minimal ground truth data.  Although WorldView-3 cannot provide the wall-to-wall coverage required for monitoring large areas, it provided robust, local training data for the Landsat-based indices to classify residue cover over the entire watershed.

See more from this Division: SSSA Division: Soil and Water Management and Conservation
See more from this Session: Soil and Water Management and Conservation Poster II

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