Mapping Tillage Practices Using Spatial Information Techniques

Area of Science:

• Agricultural Science
• Remote Sensing
• Environmental Science

Background:

• Monitoring tillage practices is key for understanding soil quality, yield, and environmental impacts.
• Accurate residue maps are scarce, hindering effective sustainable residue management.
• Predictive insights into soil quality dynamics are vital for agricultural planning.

Purpose of the Study:

• To develop and validate a remote sensing-based technique for assessing surface residue cover.
• To create an empirical model integrating field measurements and satellite data for residue mapping.
• To address the scarcity of accurate residue maps for improved soil and environmental management.

Main Methods:

• Integrated line-transect residue cover measurements with ground spectroradiometer and Advanced Wide-Field Sensor (AWiFS) satellite imagery.
• Developed an empirical model for mapping surface residue cover.
• Validated the residue map using non-photosynthetic vegetation (NPV) fractional component extracted by spectral mixture analysis (SMA).

Main Results:

• Achieved a high correlation (R² = 87%) between field residue estimates and the satellite-derived map.
• Categorization of a large-scale AWiFS imagery (836,868 ha) in South Dakota revealed <4% of corn fields had >15% surface residue cover by November 2009.
• The study demonstrated the feasibility of using remote sensing for large-area residue assessment.

Conclusions:

• The developed remote sensing technique provides an accurate method for mapping surface residue cover.
• Findings can inform policy decisions regarding soil quality and residue management.
• Future work includes mapping residues for other crops and seasons and investigating hyperspectral data integration.