Combines remote sensing, process based ecosystem modeling, and machine learning to generate spatially-explicit assessments of soil properties and biogeochemical processes that quantify carbon and nitrogen cycling and greenhouse gas fluxes across croplands and grasslands, with applications from field to regional scales for informing regenerative agricultural strategies.