Hyperspectral sensing and AI pave new path for monitoring soil carbon

Just how much carbon is in the soil? That’s a tough question to answer at large spatial scales, but understanding soil organic carbon at regional, national, or global scales could help scientists predict overall soil health, crop productivity, and even worldwide carbon cycles. University of Illinois researchers show new machine-learning methods based on laboratory soil hyperspectral data could supply equally accurate estimates of soil organic carbon.