Predicting Soil Health Across New York: New Data Tools for Smarter Land Use and Resilient Farming

Three key factors shape soil health: what nature gave you, how the land is used, and how it’s managed.

Healthy soils are essential for agriculture, clean water, and climate adaptation, but they vary across landscapes and change over time. Until now, it’s been difficult to disentangle all the important factors (climate, inherent soil properties, and land use and management) that influence soil health. Cornell Soil Health researchers have developed new machine learning models by analyzing a large dataset of soil health results from across NYS. These models enable us to estimate soil health in areas that haven’t been sampled and to predict the impacts of various land-use decisions.

Highlights

• Soil health can be mapped statewide using data-driven models that integrate climate, land use, and inherent soil properties
• Land use and management explain between 42%-58% of soil health variation—showing that how we manage land has a major impact
• Practices that increase biomass inputs, like using cover crops, rotating with perennials, and adding manure, contribute to stronger soil health outcomes.

For full methods and findings, see the peer-reviewed article in Geoderma:
Digitally mapping soil health at regional scale: disentangling drivers and predicting spatial land use effects