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.
@article{arxiv.2604.14652,
title = {DigiForest: Digital Analytics and Robotics for Sustainable Forestry},
author = {Marco Camurri and Enrico Tomelleri and Matías Mattamala and Sebastián Barbas Laina and Martin Jacquet and Jens Behley and Sunni Kanta Prasad Kushwaha and Fang Nan and Nived Chebrolu and Leonard Freißmuth and Marvin Chayton Harms and Meher V. R. Malladi and Fan Yang and Jonas Frey and Cesar Cadena and Marco Hutter and Janine Schweier and Kostas Alexis and Cyrill Stachniss and Maurice Fallon and Stefan Leutenegger},
journal= {arXiv preprint arXiv:2604.14652},
year = {2026}
}