Remote-sensing-driven GHG emission models for large-scale agriculture

Deep learning models that combine satellite imagery with on-site chamber sensor data to estimate N2O, CH4, and CO2 fluxes from agricultural fields at high spatiotemporal resolution, reducing infrastructure costs and enab...