Soil Organic Carbon

Our approach combines soil organic carbon (SOC) models with remote sensing to help carbon project developers, government entities, and verification bodies efficiently measure, estimate, and predict soil organic carbon. This method leverages the power of 140 predictors and allows for significantly reducing the number of expensive physical soil samples needed for verification. The extensive range of predictors, including satellite imagery, greatly improves the accuracy of SOC estimations. Join us in exploring how our model is contributing to the realm of measuring soil carbon while aiding in the pursuit of a sustainable future.

You can use our SOC model to:

• Save on soil sampling and increase profits from carbon credit generation.
• Use it as baseline for the carbon credit generation and creating a more positive footprint while increasing profit.
• Create accurate soil maps that illustrate its nutrient content, pH, etc.
• Optimize resource allocation (people, money, inputs, time) by upgrading farming activities to carbon sequestration MRV practices.