DigiForest: Digital Analytics and Robotics for Sustainable Forestry

TL;DR

DigiForest introduces a comprehensive digital and robotic system for sustainable forestry, combining autonomous data collection, forest inventory, decision support, and low-impact logging validated in European forests.

Contribution

It presents a novel large-scale precision forestry approach integrating diverse autonomous robots and digital tools for sustainable forest management.

Findings

Validated in forests in Finland, UK, and Switzerland.

Effective autonomous tree data collection and forest inventory.

Supports sustainable decision-making and low-impact logging.

Abstract

Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and woodlands reach approximately 40% of land area, and the forestry sector is central to achieving the EU's climate neutrality and biodiversity goals; these emphasize sustainable forest management, increased use of long-lived wood products, and resilient forest ecosystems. To meet these goals and properly address their inherent challenges, current practices require further innovation. This chapter introduces DigiForest, a novel, large-scale precision forestry approach leveraging digital technologies and autonomous robotics. DigiForest is structured around four main components: (1) autonomous, heterogeneous mobile robots (aerial, legged, and marsupial) for tree-level data collection; (2) automated extraction of tree traits to build forest inventories; (3) a Decision Support System (DSS) for forecasting forest growth and supporting decision-making; and (4) low-impact selective logging using purpose-built autonomous harvesters. These technologies have been extensively validated in real-world conditions in several locations, including forests in Finland, the UK, and Switzerland.