The flagship project will develop a sovereign, AI enabled geospatial digital twin that fuses satellite Earth observation, Internet of Things and sensor streams, climate records and agronomic models into a shared digital environment representing Australia's agricultural landscapes as a whole of agriculture system.
By functioning as a dynamic virtual replica of real world conditions, the digital twin is designed as a living research and development engine that enables faster, lower risk innovation while supporting long term productivity growth, resilience and sustainability across the sector.
The platform's AI driven analytics and modelling tools will support predictive scenario exploration for climate resilience, biosecurity, water resource management and farm productivity, allowing decision makers to test options, assess risks and optimise interventions before they are implemented on the ground.
Elders, Meat and Livestock Australia and Charles Sturt University are supporting the initiative, positioning the twin as a shared national asset that can be used by producers, advisers, researchers, industry groups and policy makers.
Professor Andy Koronios, founding chief executive and managing director of the Australasian Space Innovation Institute, said Australia has world class capability in agriculture, forestry and fisheries but lacks a shared national system that can turn that strength into decision ready insight at scale.
He said the National Digital Twin provides that missing layer as a sovereign, AI enabled environment where Australia can model scenarios, test outcomes and make better decisions across productivity, resilience and policy, describing it as national infrastructure for public good best stewarded by an independent, not for profit institute for the benefit of the nation.
Meat and Livestock Australia managing director Mick Crowley said the digital twin creates the foundation for a virtual research and development capability in which scenario modelling and hypothesis testing can occur inside a replica of agricultural environments before large scale trials or commercial deployments proceed.
He said using the twin to test livestock management options and research questions can allow teams to refine trial designs in advance, saving millions of dollars and years of research time compared with traditional methods while increasing confidence in solutions rolled out at scale.
Charles Sturt University vice chancellor Professor Renee Leon said the National Digital Twin for Australian Agriculture represents an important step forward for the sector and aligns with the Australian Agricultural Data Exchange hosted by the university, which is already demonstrating the value of bringing together key agricultural datasets.
She said the data exchange and the National Digital Twin will operate jointly to turn fragmented agricultural data into scalable, trusted outcomes for research, industry and policy, giving experts the linked information they need to run more effective experiments, test hypotheses and refine trials.
Elders managing director and chief executive and Australasian Space Innovation Institute board member Mark Allison said Elders' strength has always come from its people and relationships with farmers, and the National Digital Twin builds on that by providing agronomists, advisers and agtech providers with access to trusted, nationally consistent intelligence.
He said the twin offers a powerful environment to test and refine ideas before they reach the paddock, aiming to strengthen the quality of advice that can be offered while ensuring that relationships and professional judgement remain firmly with the adviser.
The Australasian Space Innovation Institute describes the National Digital Twin for Australian Agriculture as the first major project for the newly formed institute and positions it as a long term national capability that will evolve as more data sources, models and use cases are integrated over time.
Related Links
Australasian Space Innovation Institute
Earth Observation News - Suppiliers, Technology and Application
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