| Abstract |
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. |