Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

108315 Combining Landsat-8 and Worldview-3 Data to Assess Crop Residue Cover.

Poster Number 1035

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

Monday, October 23, 2017
Tampa Convention Center, East Exhibit Hall

Craig S. T. Daughtry, 10300 Baltimore Ave, USDA-ARS, Beltsville, MD, Alan Stern, USDA-ARSHydrology and Remote Sensing Lab, Beltsville, MD, W. Dean Hively, USGS, Beltsville, MD and Andrew L. Russ, 10300 Baltimore Avenue BARC-W, USDA-ARS, Beltsville, MD
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. 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. Currently, no program exists for objectively monitoring crop residue cover or tillage intensity at field to watershed scales. Spectral indices that detect absorption features associated with cellulose and lignin in crop residues can provide reliable assessments of crop residue cover. However, current multispectral satellite sensors either lack appropriate spectral bands to reliably distinguish crop residues from soil or cannot provide wall-to-wall coverage.

Our objective was to estimate crop residue cover and tillage intensity in corn and soybean fields by combining data from two multispectral satellites. We measured crop residue cover in two locations/field in >45 fields using the line-point transect method. Landsat-8 and WorldView-3 images were acquired within 10 days of the field measurements and corrected to surface reflectance. The Landsat Normalized Difference Tillage Index (NDTI) required local calibrations to account for changes in soils, crops, and scene moisture. In contrast, the WorldView-3 Shortwave Infrared Normalized Difference Residue Index (SINDRI) reliably estimated crop residue cover with minimal ground truth data. Although WorldView-3 images cannot provide wall-to-wall coverage, they can augment and extend ground truth observations for calibrating the Landsat and Sentinel-2 tillage indices. Classifications of tillage intensity corresponding to conventional tillage (<30% residue cover) and conservation tillage (≥30% residue cover) were significantly better than random using either Landsat-8 data only or Landsat-8 plus WorldView-3 data. The contribution of the WorldView-3 data significantly reduced the number of ground truth samples required for calibrating the Landsat tillage indices.

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