用机器人和数字技术实现精准可持续林业管理
DigiForest: Digital Analytics and Robotics for Sustainable Forestry
- 部署空地协同机器人采集树木级数据
- 构建森林档案并预测生长，支持科学决策
- 适合关注智能林业与碳中和的从业者
地球陆地面积的三分之一被森林覆盖，对全球生物多样性、气候调节及人类福祉至关重要。欧洲森林与林地占陆地面积约40%，林业在实现欧盟气候中和与生物多样性目标中具有关键作用，强调可持续森林管理、长寿命木制品利用及韧性森林生态系统建设。为应对这些目标带来的挑战，需进一步创新现有实践。本文介绍DigiForest——一种基于数字技术与自主机器人的大规模精准林业新方法，包含四大核心：（1）空中、腿式与袋鼠式异构移动机器人进行树级数据采集；（2）自动化提取树体特征构建森林清查档案；（3）决策支持系统（DSS）用于森林生长预测与辅助决策；（4）专用自主采伐机实现低影响选择性采伐。上述技术已在芬兰、英国和瑞士多个真实林区完成验证。
原文摘要 · Abstract (English)
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.
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