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

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 ruggedness and battery life, ergonomic constraints, poor interoperability, and limited validation. AR nevertheless shows strong potential as a human-centred interface, but wider deployment will require forest-adapted localisation, lightweight 3D visualisation, stronger system integration, and closer collaboration across stakeholders.

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Publication Details

Journal
Current Forestry Reports
Published
2026-07-23
DOI
https://doi.org/10.1007/s40725-026-00283-x
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Alberto Udali, Pedro Caldas Britto, Raquel Lobo‐do‐Vale, Frederico Tupinambá‐Simões et al.
Current Forestry Reports
Remote Sensing and LiDAR Applications
article

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

Alberto Udali, Pedro Caldas Britto, Raquel Lobo‐do‐Vale, Frederico Tupinambá‐Simões, Felipe Bravo, Thomas Purfürst, Milutin Milenković, Emilia Tcherkezova, Alexander Kaulen, Mauricio Acuña, Karol Tomczak, P. L. Chambers, Zennure Uçar, Francesco Latterini, Oleksandr Soshenskyi, Ebru Bilici, Felipe de Miguel-Díez, Lukas Stopfer, Martino Rogai, Yannik Wardius, Funda Yildirim, Avinash Shanmugam, Safia El-Alami
article en

Abstract

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 ruggedness and battery life, ergonomic constraints, poor interoperability, and limited validation. AR nevertheless shows strong potential as a human-centred interface, but wider deployment will require forest-adapted localisation, lightweight 3D visualisation, stronger system integration, and closer collaboration across stakeholders.

Current Forestry ReportsVol. 12(1)
Universidad de Valladolid (ES), International Institute for Applied Systems Analysis (AT), University of Padua (IT), University of Lisbon (PT), Giresun University (TR), University of Freiburg (DE), University of the Sunshine Coast (AU), University of Eastern Finland (FI), Ukrainian National Forestry University (UA), National University of Life and Environmental Sciences of Ukraine (UA), University of Évora (PT), Bulgarian Academy of Sciences (BG), Izmir Kâtip Çelebi University (TR), Natural Resources Institute Finland (FI), National Institute of Geophysics, Geodesy and Geography (BG), Institute of Dendrology (PL), Institute of Biosciences and Bioresources (IT), Poznan Supercomputing and Networking Center (PL), Forest Research (GB), Supply Chain Competence Center (Germany) (DE), Łukasiewicz Research Network - Wood Technology Institute (PL), National Research Council (IT), Łukasiewicz Research Network - Poznań Institute of Technology (PL), Poznań University of Technology (PL), University of Life Sciences in Poznań (PL), Technische Universität Dresden (DE), University of Twente (NL), Polish Academy of Sciences (PL)
Baden-Württemberg Stiftung, Technische Universität Dresden, Österreichische Forschungsförderungsgesellschaft, Bundesministerium für Ernährung und Landwirtschaft, Fachagentur Nachwachsende Rohstoffe, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 15%
Remote Sensing and LiDAR Applications
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