Cover Crops in Pennsylvania
Several bins of varied winter vegetation cover are defined using NDVI thresholds in Pennsylvania

Despite the monumental challenges posed by climate change and the incredible promise of soil carbon sequestration, the world is still far away from the widespread adoption of regenerative farming practices. This isn't surprising given that current approaches are fraught with friction.

For farmers, registering into a carbon program can feel like trying to file taxes. For folks renting ground for the first time, the lack of historical data means they don't have an established baseline. For buyers, trust can be a major issue.

Thankfully, remote sensing has the potential to address these issues and create a data-driven experience that's frictionless to the farmer, trustworthy to the buyer, and economically scalable for all parties.

Why use remote sensing for regenerative agriculture

Remote sensing can lighten the administrative burden and information transfer load from farmers to purchasers. It provides transparency, insights, and ways to scale the information for carbon markets, practice management, and other ways to monetize on a larger scale.

The benefits of remote sensing include:

  • Seeing beyond visible light--our eyes can only see the visible light spectrum. Remote sensing can look beyond and capture information about the world in infrared, microwave, and radio frequencies.
  • Satellite data collection, globally--data collection is always on thereby it can be used in models to fill knowledge gaps
  • Ability to scale ground truth data over large areas to detect cover crops, crop residue, and crop rotation practices
  • A historical record--in many cases, satellite data history can go back 5+ years or more

The power of our platform in scaling ground truth

Descartes Labs infuses the ground truth data collected from farmers and suppliers with satellite data to calibrate global observations that can be used for your areas of interest. Paired with enough ground truth, our remote sensing datasets and machine learning models have the potential to scale outside the original area of study from local to regional.

In a recent webinar, Descartes Labs joined SAI Platform to share our perspective on regenerative practices through remote sensing and machine learning. Watch the full recording for in-depth insights but here are a few takeaways:

  • For a farmer, there is a lot of information that can be lost. Remote sensing can give transparency and information that can be shared with traders and manufacturers.
  • Remote sensing is the bridge to quantifying the impact of a farm-level practice with the ability to measure through an analytics method.
  • The first step in using remote sensing starts with understanding the value of the ground truth, which means knowing what information is high leverage to collect. Combining that with remote sensing data, you can then begin to make it useful in guiding your decisions.

Webinar clip: Remote Sensing’s Role in Scaling Regenerative Agriculture

Watch the webinar in full for more insights, a demonstration of our geoprocessing platform in action along with interactive questions from the audience that could also be top of mind for you.