Apr 16, 2026 · cs.ROJ/K move · Enter open · S save
Marco Camurri, Enrico Tomelleri, Matías Mattamala, Sebastián Barbas Laina+17
Dipartimento di Ingegneria Industriale, University of Trento, via Sommarive 9, 38123 Trento (TN), Italy · Faculty of Engineering, Free University of Bozen-Bolzano, via Bruno Buozzi 1, 39100 Bozen-Bolzano (BZ), Italy · Faculty of Agricultural, Environmental and Food Sciences, Free University of Bozen-Bolzano, piazza Universit`a 5, 39100 Bozen-Bolzano (BZ), Italy · Competence Centre for Mountain Innovation Ecosystems, via Bruno Buozzi 1, 39100 Bozen-Bolzano (BZ), Italy · School of Informatics, University of Edinburgh, 10 Crichton St, EH8 9AB, United Kingdom
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.