How Agriculture and Agri-Food Canada built a cloud-based coherence change detection solution with AWS

This article describes how Agriculture and Agri-Food Canada (AAFC) built a cloud-based solution using AWS to detect changes in agricultural practices through satellite imagery analysis.

• Uses coherence change detection (CCD) on Sentinel-1 SAR satellite data to track tillage and harvest events
• Deployed on AWS using Lambda, S3, DynamoDB, Step Functions, ECS with Fargate, and ECR
• Processes satellite imagery automatically using containerized ESA SNAP application
• Completed one month of analysis across 272 scene pairs in 12 hours for approximately $200
• Enables monitoring of soil health, conservation tillage, and crop residue across Canada
• Event-driven architecture triggers processing when new satellite data arrives in S3
• Scalable from small test areas to national coverage without manual intervention

The solution demonstrates how cloud automation transforms Earth observation science into scalable workflows for agricultural monitoring and environmental policy support.