Applications of Advanced Technologies for Improved Precision in Forest Operations
A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Operations and Engineering".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 1824
Special Issue Editors
Interests: optimization methods in forestry; wood supply chain management and optimization; sensing technology; AI and automation in forestry
Special Issues, Collections and Topics in MDPI journals
Interests: forestry and harvesting; logistic of wood procurement; discrete-event simulation and drones
Interests: digitalization of forestry; forest 4.0 optimization; integration of new potential and supporting decision making for the entire forest supply chain; evaluation and optimization of technological impact for operations in forests; optimization of processes and processing steps; interaction between humans and their forestry operations
Special Issue Information
Dear Colleagues,
Forest operations have undergone profound transformations with the integration of advanced technologies to achieve superior precision in decision making. Sensing technologies like lidar, stereo cameras, and radar are crucial to this evolution, collectively contributing to a heightened perception of the forest environment. Lidar's laser-based mapping capabilities provide intricate details about the topography and tree structure, while stereo cameras and radar offer depth information, adding layers of intricacy to spatial understanding and further refining the comprehension of the forest's composition. In tandem with these sensing technologies, advanced global navigation satellite systems (GNSS) ensure the precise location tracking of machines, trees, and infrastructure, forming a foundational element of efficient forest management. The synergy extends to robotic systems and autonomous vehicles that leverage these precise measurements to navigate and operate seamlessly within the forest terrain. Advanced location and path algorithms further optimize operations, enabling vehicles to adapt dynamically to changing conditions. Moreover, the integration of tree machine learning (ML) and artificial intelligence (AI) detection algorithms enhances the specificity of data, enabling targeted assessments of individual trees. This integration of precise positioning technology improves the efficiency of harvesting, transport, and road operations and facilitates better planning and management by providing real-time spatial data. In addition, this holistic integration of technologies marks a paradigm shift towards precision, efficiency, sustainability, and harmonious coexistence between technological advancements and delicate forest ecosystems.
Potential topics include, but are not limited to:
- Use of sensing technology (e.g., lidar, depth/RGB cameras, radar) for improved forest operations
- ML and AI algorithms and applications for tree detection and mapping of the forest operations environment
- Applications of advanced technologies for the location of machines, trees, and infrastructure
- Planning of operations using remote and short-range sensing technology and optimization algorithms
- Impact of driver-assisting sensing technologies on productivity and safety
- Robotic systems and autonomous vehicles guided by sensors
Prof. Dr. Mauricio Acuna
Dr. Kari Väätäinen
Prof. Dr. Thomas Purfürst
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sensing technologies
- AI, ML, and optimization algorithms in forest operations
- location of trees and harvesting equipment
- forest operations planning using sensing technologies
- driver-assistance sensing technologies
- robotic systems and autonomous vehicles
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