Augmented Reality in Forestry: Current Capabilities, Limitations, and Future Directions

作者：Felipe de Miguel-Díez, Alberto Udali, Francesco Latterini, Frederico Tupinambá‐Simões, P. L. Chambers, Karol Tomczak, Zennure Uçar, Raquel Lobo‐do‐Vale, Yannik Wardius, Funda Yildirim, Ebru Bilici, Emilia Tcherkezova, Felipe Bravo, Oleksandr Soshenskyi, Safia El-Alami, Lukas Stopfer, Martino Rogai, Pedro Caldas Britto, Milutin Milenković, Avinash Shanmugam, Alexander Kaulen, Mauricio Acuña, Thomas Purfürst · 发表于：Current Forestry Reports · 年份：2026 · DOI：10.1007/s40725-026-00283-x · 研究领域：Remote Sensing and LiDAR Applications、Tree Root and Stability Studies、Seedling growth and survival studies

Abstract Purpose of the Review This semi-systematic review examines how augmented reality (AR) was developed and applied in forestry between 2000 and 2025. With a European focus and international scope, it integrates peer-reviewed literature, grey literature, and commercially available tools to capture progress and practice. It maps AR use cases, characterises hardware, software, and data pipelines, assesses Technology Readiness Levels, and identifies barriers, research gaps, and priorities for future deployment. Recent Findings AR in forestry is moving from isolated prototypes towards early operational implementation. The most mature applications are found in forest inventory, urban forestry, and roundwood measurement, where smartphone- and tablet-based tools using Light Detection and Ranging (LiDAR), Red, Green, Blue, and Depth (RGB-D) sensing, Simultaneous Localisation and Mapping (SLAM), and computer vision have reached moderate to high readiness, with some commercially deployed. Head-mounted displays and machine-integrated systems are being tested for stand visualisation, digital tree marking, planting guidance, and harvesting support, but most remain at pilot stage. Most systems cluster around TRL 4–6, while only a limited subset reaches TRL 7–9. Summary AR in forestry is a heterogeneous but rapidly evolving ecosystem of mobile, wearable, and machine-integrated solutions. Persistent barriers include under-canopy tracking instability, weak georeferencing, limited ruggedn...