The Australasian Space Innovation Institute (ASII) has unveiled its first flagship project, a National Digital Twin for Australian Agriculture designed to lift productivity, strengthen resilience and accelerate growth across the sector.
Backed by Elders, Meat & Livestock Australia (MLA) and Charles Sturt University, the $15 million initiative aims to build the country’s first sovereign AI-enabled virtual model of our agriculture, forestry and fisheries landscapes.
The National Digital Twin will to act as a living R&D engine for the sector, with AI-enabled capability that allows predictive scenario modelling, enabling decision-makers to test options, anticipate risks and optimise actions before implementation. The system will support innovation in areas such as climate resilience modelling, biosecurity, water management and productivity.
ASII’s founding CEO and Managing Director Professor Andy Koronios said the initiative would deliver a vital national capability.
“Australia has world-class agricultural, forestry and fisheries capability, but we lack a shared national capability to turn that strength into decision-ready insight at scale,” Professor Koronios said.
“The National Digital Twin provides that missing layer: a sovereign, AI-enabled environment where Australia can model scenarios, test outcomes, and make better decisions across productivity, resilience and policy. It is a national infrastructure for public good, best stewarded by an independent, not-for-profit institute like the ASII, for the benefit of the nation.”
The digital twin will integrate data from satellite Earth Observation, sensor and IoT systems, climate data and agronomic models into a shared digital environment. The result will be a dynamic, national-scale view of Australia’s agricultural landscapes.
MLA Managing Director Mick Crowley said the digital twin will dramatically change how agricultural research and development is done.
“The Digital Twin creates the foundation for a new virtual R&D capability: scenario modelling and hypothesis testing inside a replica of agricultural environments. That means we can test livestock management options and research questions faster, refine trials before we invest in large scale field trials, adoption or commercialisation,” Mr Crowley said.
“Done well, this approach can save millions of dollars and years of research time compared with traditional methods, while lifting confidence in what we deploy at scale.”
The digital twin will play an important role in bringing together Australia’s fragmented agricultural data and turning it into trusted, accessible intelligence to inform research, industry and policy.
As more research, models and data are added, the platform is expected to become a long‑term national asset designed to support better decisions and faster, lower‑risk innovation across the agricultural sector.
