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Main Authors: Camurri, Marco, Tomelleri, Enrico, Mattamala, Matías, Laina, Sebastián Barbas, Jacquet, Martin, Behley, Jens, Kushwaha, Sunni Kanta Prasad, Nan, Fang, Chebrolu, Nived, Freißmuth, Leonard, Harms, Marvin Chayton, Malladi, Meher V. R., Yang, Fan, Frey, Jonas, Cadena, Cesar, Hutter, Marco, Schweier, Janine, Alexis, Kostas, Stachniss, Cyrill, Fallon, Maurice, Leutenegger, Stefan
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.14652
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author Camurri, Marco
Tomelleri, Enrico
Mattamala, Matías
Laina, Sebastián Barbas
Jacquet, Martin
Behley, Jens
Kushwaha, Sunni Kanta Prasad
Nan, Fang
Chebrolu, Nived
Freißmuth, Leonard
Harms, Marvin Chayton
Malladi, Meher V. R.
Yang, Fan
Frey, Jonas
Cadena, Cesar
Hutter, Marco
Schweier, Janine
Alexis, Kostas
Stachniss, Cyrill
Fallon, Maurice
Leutenegger, Stefan
author_facet Camurri, Marco
Tomelleri, Enrico
Mattamala, Matías
Laina, Sebastián Barbas
Jacquet, Martin
Behley, Jens
Kushwaha, Sunni Kanta Prasad
Nan, Fang
Chebrolu, Nived
Freißmuth, Leonard
Harms, Marvin Chayton
Malladi, Meher V. R.
Yang, Fan
Frey, Jonas
Cadena, Cesar
Hutter, Marco
Schweier, Janine
Alexis, Kostas
Stachniss, Cyrill
Fallon, Maurice
Leutenegger, Stefan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2604_14652
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle DigiForest: Digital Analytics and Robotics for Sustainable Forestry
Camurri, Marco
Tomelleri, Enrico
Mattamala, Matías
Laina, Sebastián Barbas
Jacquet, Martin
Behley, Jens
Kushwaha, Sunni Kanta Prasad
Nan, Fang
Chebrolu, Nived
Freißmuth, Leonard
Harms, Marvin Chayton
Malladi, Meher V. R.
Yang, Fan
Frey, Jonas
Cadena, Cesar
Hutter, Marco
Schweier, Janine
Alexis, Kostas
Stachniss, Cyrill
Fallon, Maurice
Leutenegger, Stefan
Robotics
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.
title DigiForest: Digital Analytics and Robotics for Sustainable Forestry
topic Robotics
url https://arxiv.org/abs/2604.14652