Soil Health Digital Tools on the Way

Digital Record Keeping, High-Resolution Satellite Images, and Modeling Soil Pests Will Help Farmers Better Gauge Soil Health.

Wondering how to gauge soil health? Well, digital tools will play a role in assessing and monitoring soil health, says Brian Lutz, director of modeling at The Climate Corporation.

Tools include:

 Digital record keeping. “We have long measured soil organic matter through standard soil tests,” Lutz says. “But one of the biggest challenges with soil tests historically is every time we test the soil, we can lose the paperwork. Or, we don’t go back to see how soils are changing over time because it’s harder to track with paper. If we digitize soil data, it’s much easier to see how soils change over time.”

High-resolution satellite images. The Climate Corporation has been testing high-resolution soil organic matter maps derived from satellite images. These can more accurately pinpoint soil health qualities, says Lutz.  

“We’re finding that satellite imagery gives us highly accurate measurements of soil organic matter,” he says. 

That’s because soil samplers often manually collect samples on 2.5-acre grids. Satellite imagery drills down much further by sampling to 10×10-meter grids. Satellite imagery will also enable farmers to better detect physical properties that impact soil health, such as soil compaction or lack of drainage. The Climate Corporation also plans to use satellite imagery to better measure soil pH and cation exchange capacity (CEC).

“This gives us a window into the soil that we haven’t had in the past,” he says. 

Modeling soil pests. Soil may seem dull as well, dirt. Underneath one’s feet, though, is a sea of soil life ranging from bacteria to viruses to fungi to earthworms. The Climate Corporation is using tools like artificial intelligence and object-based recognition to better assess this soil life, says Lutz. 

“Another aspect will be detecting harmful soil organisms, such as corn rootworm and other pests that can cause tremendous yield loss,” says Lutz. “Through data science, we can better model and estimate where those pressures will be greatest so that we can help growers place the right seed products in those fields.” 

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