Felipe de Miguel-Díez

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.

Forest planning and operational execution still often rely on separate office-based workflows, field inventories, and analogue tree-marking procedures, limiting direct communication between planners and field personnel. Mixed reality (MR) interfaces and forest digital twin concepts may help link planning decisions with field-level visualization and interaction. This study presents an initial proof-of-concept prototype for MR-based virtual tree tagging and field–office communication in forestry. The prototype integrates a Unity GE-based Forest Planner System, a Microsoft HoloLens 2-based Forest Worker System, and a locally hosted MagicOnion server for bidirectional client–server communication. Virtual trees with predefined stem diameters were created in Unity GE, and torus-shaped markers were implemented to support tree selection, color-coded designation, marker deletion, and visualization of predefined diameter-related attributes. Under controlled indoor conditions using a 5G mobile hotspot, both clients connected to the server and exchanged marker-related events. Marker creation, color assignment, deletion, and shared marker-state updates initiated from either client were reproduced in the corresponding system. The prototype demonstrates the functional feasibility of the core communication workflow but remains limited to a simulated environment.

Introduction: Vital to forest management, forest roads enable operations such as timber harvesting, fire protection, and recreational access. However, their functionality is threatened by insufficient maintenance driven by limited financial and human resources, and constraints related to the availability and quality of information, as well as suitable tools for systematic condition assessment. Traditional visual inspections are widely used in Germany but are subjective, inconsistent, and difficult to scale. This study examines stakeholder perspectives on implementing a digital forest road condition monitoring system to support predictive maintenance approaches. Methods: To evaluate the feasibility and stakeholder acceptance, semi-structured qualitative interviews were conducted with 30 representatives from five stakeholder categories across Germany. Thematic content analysis was applied to assess current maintenance practices, data needs, technical and legal constraints, and the stakeholders’ willingness to contribute across stages of the system (data collection, processing, provision, and use). Results: Stakeholders broadly recognized the potential value of digital forest road condition data for planning maintenance, estimating costs, and improving navigation. However, adoption is constrained by limited digital competence and staffing, financial barriers, data protection and access-right concerns, and coordination challenges associated with fragmented forest ownership. Participants emphasized the need for reliable, standardized, and user-friendly solutions, and highlighted that long-term implementation depends on viable business model configurations (e.g., subscription or pay-per-use access models and remuneration schemes for data collection, such as flat rate) spanning multiple stakeholders. Discussion: By aligning stakeholder interests and addressing legal, technical, and financial barriers, such configurations can enable the long-term operability of digital forest roads monitoring systems. These findings provide a qualitative foundation for developing scalable implementation concepts and business model configurations for digital forest road monitoring that are transferable beyond the German context.

Background: There is a clearly increasing trend of wildfires that become catastrophic in some countries such as the United States, Australia, Russia, Portugal, Greece, and Spain. Fuel is one of the key components that influences fire behavior and its effects. Assessing the fuel load and distribution of its components in the landscape provides effective fire management treatments in terms of fire prevention campaigns on a scientific basis. This study aims to evaluate the litter, duff, and herb fuels in highly flammable coniferous forest types in Ukrainian Polissia. To estimate relationships between forestry variables that reflect the characteristics of the pine stand (DBH, height of the stand, age, relative density, stock of the plantation etc.) and the load of litter, duff, and herb fuels (CWD, FWD, litter, live grass, etc.), correlation analysis was used. To analyze difference between groups of sampling plots that have different forests, we use generalized linear mixed models including random effects of sampling plot type. Cluster analysis was performed using k-means partitioning method and Calinski-Harabasz criterion. To assess the significance of individual variables on which the variation of forest fuel depends, the random forest algorithm was used; for variable selection, we used two parameters: the percent increase in mean squared error and the Gini impurity index. Results: The research revealed that in the pine forest stands, the stock of litter and duff varies from 15.5 (15 years) to 140 ton/ha (139 years). When modeling, the humidity level of the forest site (soil) significantly affects the dynamics of forest fuel accumulation. In fresh types of forest-growing conditions, the forest litter stock increases to the age of 80–90 years; then, it strongly decreases, while in wet forest types, continuous forest fuel stock accumulation is established during the entire growth period. Moreover, the results showed that the forest fuel load was influenced by the soil fertility. The stock of live and dead herbaceous fuel in fresh and wet conditions is not statistically different, and soil moisture has not had a significant impact. Fine woody debris stocks were more dependent on stand productivity and practically does not depend on the soil fertility index, site moisture content, and its age and ranged from 0.4 to 1.9 t/ha (1 h), from 0.1 to 2.2 t/ha (10 h), and from 0 to 1.6 t/ha (100 h). Conclusions: The obtained results enabled to develop mathematical models for estimating litter and duff stocks in the Polissia forest stands based on stand characteristic and the soil humidity level. Moreover, the results will serve as basis to develop local forest fuel models as well as to determine potential fire hazards and a fire behavior modeling process in coniferous forests of that region. These models constitute the basis for the national set of fuel model development for each nature zone of Ukraine.

In commercial transaction of stacked roundwood, the estimation of the stack net volume plays a key role. One generalized method to determine the net volume is using conversion factors that relate the gross and net volumes. In this literature review the developed methods to estimate the conversion factors as well as their influencing parameters were analyzed based on 153 references from America and Europe. According to the results, 48 different methods (including their variants) for estimating the conversion factors were developed. The newest methods enabled their accurate determination inexpensively, e.g., photo-optical methods or 3D simulation models. The analyzed references revealed that 30 parameters influence the conversion factors. Based on this comprehensive review, each stakeholder involved in the roundwood supply chain can know which method is used for estimating the conversion factors in the analyzed territories and which influencing parameters should be considered when purchasing roundwood in order to accurately assess the solid wood content in the stacks.

Assessing the solid wood content is crucial when acquiring stacked roundwood. A frequently used method for this is to multiply determined conversion factors by the measured gross volume. However, the conversion factors are influenced by several log and stack parameters. Although these parameters have been identified and studied, their individual influence has not yet been analyzed using a broad statistical basis. This is due to the considerable financial resources that the data collection entails. To overcome this shortcoming, a 3D-simulation model was developed. It generates virtual wood stacks of randomized composition based on one individual data set of logs, which may be real or defined by the user. In this study, the development and evaluation of the simulation model are presented. The model was evaluated by conducting a sensitivity and a quantitative analysis of the simulation outcomes based on real measurements of 405 logs of Norway spruce and 20 stacks constituted with these. The results of the simulation outcomes revealed a small overestimation of the net volume of real stacks: by 1.2% for net volume over bark and by 3.2% for net volume under bark. Furthermore, according to the calculated mean bias error (MBE), the model underestimates the gross volume by 0.02%. In addition, the results of the sensitivity analysis confirmed the capability of the model to adequately consider variations in the input parameters and to provide reliable outcomes.

One method for estimating the solid wood content in a stack involves using conversion factors and multiplying these by the measured gross volume. The conversion factors can vary depending on several log and stack parameters. The aim of this study was to analyze eleven parameters using a 3D simulation model based on 541 measured logs of Norway spruce. To this end, 50 data sets were created from measured logs, where the parameters of interest in this study (e.g., length, crookedness, taper …) were classified according to different ranges. After that, 64 runs of simulations were carried out. In each simulation run, 150 stacks were modeled. The simulation results were compared with previous studies and with the measurement guidelines of several countries. This analysis revealed that the parameters midpoint diameter, length, crookedness, delimbing quality and the proportion of moderately and highly crooked logs in a stack have a considerable influence on the conversion factors. Taper, proportion of butt logs in a stack and stack height have a modest effect as do the proportion of tapered and crooked logs for low and high taper and low crookedness. In contrast, ovality and the proportion of logs stacked in opposite directions have a marginal influence on the conversion factors. Based on findings from these analyses, the current measurement guidelines of different countries can now be adapted to achieve a higher degree of accuracy.

The influence that parameters crookedness and taper have on the stack volume was analyzed by using a 3D-simulation model in this study. To do so, log length, diameters at the midpoint and both ends, crookedness, bark thickness, taper and ovality were measured in 1000 logs of Scots pine. From this database, several data sets with different proportions of crooked and tapered logs in stack as well as with different degrees of taper and crookedness were created and taken as basis to simulate the stacks and carry out the analysis. The results show how the variation of these parameters influences the stack volume and provide their volume variation grades. These rates of variation were compared with measurement guidelines of some countries and previous research works. In conclusion, the parameters crookedness and taper influence the stack volume to a considerable extent. Specifically, the stack volume is increased as the crookedness degree or the proportion of crooked logs increases. In contrast, the stack volume is reduced as the taper degree or the proportion of tapered logs increases. Furthermore, the results demonstrate the capability of this simulation model to provide accurate results which can serve as a basis for future studies.

The accurate estimation of timber volume is of the utmost importance. For industrial timber, the volume is often estimated as stacked cubic meters. In addition to manual measurements, volume estimation is possible with photo-optical systems. Over 100 piles of industrial timber of broadleaved tree species were analyzed. In the study, a standard manual measurement method for the estimation of wood pile volumes was compared with a smartphone based photo-optical application for the determination of woodpile volume. Mean gross volume of the piles was approximately 56 m³ and mean width of piles was 9.43 m. A strong correlation was found between the manual measurements and the photo-optical measurement. However, volume estimation of large volume piles seems to perform better in comparison to piles with small volumes. Further research is needed to determine the effects of variables such as log quality or quality of pile on volume estimation accuracy.