How Satellite Imagery Helps Advance Regenerative Ag Practices

Gradable is building programs that reward producers for their regenerative practices.Farming sustainably means protecting the natural resources a farm relies on while running a healthy business. Gradable programs help farms improve nitrogen use efficiency, reduce greenhouse gas emissions, increase soil nutrients, and expand farmer profit potential. 

For decades, grain producers have led the charge with regenerative practices like cover cropping, removing or eliminating tillage, rotating crops, incorporating livestock, and promoting biodiversity. And there are more opportunities for sustainable agriculture on the horizon.


Read more about how Gradable is helping farmers become more sustainable. »

Streamlining verification & opening up new markets for farmers

Today’s farming technology allows producers to monitor their farm and business health in more detail than ever before, with data flowing seamlessly from machinery to the cloud. This data enables farmers to reach consumers in new ways by unlocking environmental attributes associated with individual bushels of production. And all farms that participate in programs are protected by Gradable’s privacy policy.

Gradable’s technology also makes verification of practices—usually time consuming and expensive—easier for growers. Machine learning and satellite imagery allow Gradable to analyze millions of acres of crop production data to support and verify crop production data. 

How does it work?

Satellite imagery combined with precipitation and temperature data helps Gradable verify cover cropping and tillage—both essential regenerative practices. We’re able to identify cover cropping with 96% accuracy (see Figure 1). 

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Figure 1. Sentinel-2 satellite imagery and Enhanced Vegetative Index (EVI) data show the difference between fields with and without cover crops.

Gradable technology is also able to correctly classify conventional tillage, reduced tillage, and no-till with an average accuracy of 77%—and 84% accuracy when classifying no-till (see Figure 2).

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Figure 2. Satellite imagery and normalized difference tillage index (NDTI) from Sentinel-2 satellite imagery demonstrating the differences between different tillage practices (Top: no-till after corn; Bottom: conventional tillage after corn).

Using satellite imagery and leading-edge farming technology, Gradable is helping reduce the costs and time associated with verification for producers to take advantage of new markets for sustainably grown crops. Gradable verification can help reduce or eliminate the need for on-site visits while maintaining high levels of accuracy.


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