Speaker
Description
As the forestry sector transitions toward the era of Forestry 4.0, the integration of digital planning into physical field operations remains a critical bottleneck. Traditionally, in high value thinning tree selection and marking, essential for sustainable forest management and selective harvesting, rely on manual application of spray paint. This analog process is not only labour-intensive but also creates a significant disconnect between digital inventory databases and the actual environment. This poster explores the transformative potential of Augmented Reality (AR) as a solution to bridge this gap by enabling the direct, real-time visualisation of digitally marked trees within the forest stand.
By leveraging high-precision Global Navigation Satellite Systems (GNSS) combined with Simultaneous Localization and Mapping (SLAM) algorithms, AR headsets and mobile devices can project "virtual paint" or holographic indicators directly onto specific tree trunks. This technology allows foresters to perform virtual selections that are immediately anchored to the physical tree, creating a persistent digital layer that is visible to harvester operators and forestry crews. Such a system eliminates the need for physical marking materials, reduces the time spent searching for designated trees in dense undergrowth, and ensures that complex silvicultural prescriptions are executed with unprecedented spatial accuracy.
Furthermore, the implementation of AR-based visualization facilitates a dynamic feedback loop; harvest plans can be updated remotely and reflected instantly in the field, allowing for agile responses to environmental changes or timber market demands. While challenges regarding hardware durability in extreme weather and signal occlusion under dense canopies persist, the transition from physical to virtual marking represents a paradigm shift in forest operations. This study concludes that AR-driven tree visualisation not only enhances operational efficiency and safety but also provides a more sustainable, data-driven framework for managing the forests of the future.
| Keywords | AugmentedReality, PrecisionForestry, DigitalTwins, ForestOperations4.0. |
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