From Roadside Surveys to Satellite-Based Maps: Mapping Tillage Practices in Eastern Washington

Machine learning and field observations improve tillage maps across diverse eastern Washington cropping systems.

Two people stand outside a car in a field, one holding crop residues and othe other holding a tablet.

This BIOAg blog post describes how researchers combined satellite imagery, machine learning, and roadside field observations to map tillage practices across eastern Washington. Existing approaches developed for the Midwest performed poorly because crop residue does not indicate tillage consistently across the region’s diverse cropping systems. Using 577 field observations and a framework that accounted for crop type, researchers increased median overall accuracy from 69% to 84%. Accuracy for legumes increased from 34% to 76%. Collaboration with Extension specialists and conservation district staff helped improve the maps and move them into practical use, including work supporting the Voluntary Stewardship Program. Subsequent research quantified uncertainty for individual fields, explored uncertainty-guided data collection, and examined how residue type and age affect satellite measurements. The team plans to use the maps in erosion and soil-carbon models and expand the approach to other dryland agricultural areas.

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Authors

Norouzi Kandelati, A.

Related Products

Related Project

Year Published

2026

Areas of Focus

Agricultural Practices and Agricultural Technology

Topics

Production Systems and Soils & Fertility

Collaborators

  • Palouse Conservation District

Funding Source