Forest ecosystem resilience is of considerable interest worldwide, particularly given the climate crisis, biodiversity loss, and recent instances of zoonotic diseases linked to deforestation and forest loss. Novel, digital-based technologies are also increasingly ubiquitous. We provide a more comprehensive understanding of how these new technologies are being used for forest management in different sectors and contexts, and discuss potential implications and future research needs for forestry researchers, managers, and policymakers. We carried out a literature database search and scoping review to collect peer-reviewed articles from 2010 to 2020, and developed a forest-technology classification to identify hardware and/or software technologies and techniques, methodology used, forest management application(s), spatial and temporal context, subsequent challenges and limitations, and opportunities. A qualitative analysis revealed a strong emphasis on remote sensing-based innovations for forest monitoring, planning, and management, where machine-learning techniques also play an important role in data collection, processing, and analysis. Data fusion approaches are also becoming more common, enabled by open-source data sets and data sharing practices. More emerging technologies and applications include virtual/augmented environments for understanding human-nature relationships and behavior patterns, automated workflows for forestry operations, and urban green infrastructure mapping and ecosystem services assessments via social media and mobile tracking applications. The continued adoption of digital-based tools will likely bring about new research questions about forest ecosystems as dynamic social, ecological, and technological landscapes, and future work should more closely examine how forestry researchers, managers, and stakeholders can anticipate and adapt to both environmental and technological uncertainty change in a forest-ecosystem context.

中文翻译：

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数字森林：绘制森林生态系统技术应用十年的知识图谱

森林生态系统的复原力在世界范围内引起了广泛关注，特别是考虑到气候危机、生物多样性丧失以及最近与森林砍伐和森林丧失有关的人畜共患疾病。新颖的、基于数字的技术也越来越普遍。我们更全面地了解这些新技术如何用于不同部门和环境中的森林管理，并讨论林业研究人员、管理者和政策制定者的潜在影响和未来研究需求。我们进行了文献数据库搜索和范围审查以收集 2010 年至 2020 年的同行评议文章，并制定了森林技术分类，以识别硬件和/或软件技术和技术、使用的方法、森林管理应用、空间和时间背景，随后的挑战和限制，以及机遇。定性分析显示，森林监测、规划和管理方面的遥感创新受到高度重视，其中机器学习技术在数据收集、处理和分析中也发挥着重要作用。在开源数据集和数据共享实践的支持下，数据融合方法也变得越来越普遍。更多新兴技术和应用包括用于理解人与自然关系和行为模式的虚拟/增强环境、林业运营的自动化工作流程，以及通过社交媒体和移动跟踪应用程序进行的城市绿色基础设施测绘和生态系统服务评估。