DigiForest: Digital Analytics and Robotics for Sustainable Forestry
A consortium's new system uses aerial, legged, and marsupial robots to build detailed 3D forest inventories.
A major academic and research consortium has introduced DigiForest, a comprehensive digital framework designed to revolutionize sustainable forest management. The system, detailed in a new 34-page paper, is built around four core technological pillars. First, it employs a fleet of heterogeneous autonomous robots—including aerial drones, legged platforms, and marsupial systems (where robots carry each other)—to collect granular, tree-level data across vast woodland areas. This data is then processed to automatically extract key tree traits like species, diameter, and height, building highly accurate 3D digital forest inventories.
The second half of the system focuses on analysis and action. A sophisticated Decision Support System (DSS) uses the collected data to model and forecast forest growth, aiding long-term management planning. Finally, the loop is closed with purpose-built autonomous harvesters designed for low-impact, selective logging operations, minimizing damage to the surrounding ecosystem. The entire DigiForest approach has been field-tested and validated under real-world conditions in diverse European forests, including sites in Finland, the United Kingdom, and Switzerland, demonstrating its practical viability for large-scale deployment.
- Uses a heterogeneous robot fleet (aerial, legged, marsupial) for detailed 3D data collection at the individual tree level.
- Integrates a Decision Support System (DSS) to forecast forest growth and guide sustainable management decisions.
- Validated in real-world deployments across forests in Finland, the UK, and Switzerland, targeting EU climate and biodiversity goals.
Why It Matters
Provides a scalable, data-driven solution for managing forests—critical carbon sinks—more sustainably and efficiently.