EO4AgroClimate - Towards a digital twin of cropping systems based on ingestion of EO into process-based crop models (EOCROP)

Ensuring resource efficient crop productivity across important global agricultural regions is crucial for future sustainable food production. New Earth Observation (EO) datasets provide exciting opportunities to calibrate crop models for application across diverse geographical regions to optimise crop management. To date these opportunities have only been realised for simple crop models or for very specific process-based crop model applications focussing on singular, specific aspects such as phenology or yield. Existing efforts have not developed a repeatable, generalisable capacity to integrate EO data into crop models. This project will develop a digital twin where a range of crop relevant EO data will be processed to describe sophisticated crop model processes for the calibration of canopy physiology, carbon allocation, biomass and yield. The resulting crop models will be appropriate for answering a range of food security and sustainability challenges such as crop resilience under climate change, resource management and GHG emission reduction.