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Forests
Special Issues
Forest Operations and Forest Road Networks Design
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Forest Operations and Forest Road Networks Design

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Operations and Engineering".

Deadline for manuscript submissions: closed (21 February 2023) | Viewed by 4611

Special Issue Editor

Prof. Dr. Kevin Boston

E-Mail Website
Guest Editor
Department of Forestry and Wildland Resources, Humboldt State University, Arcata, CA 95521, USA
Interests: optimization; simulation; modeling; rivers; linear programming; geotechnical engineering; mathematical programming; forest management; scheduling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will consider recent work in forest operations and forest road design. It will begin by describing the use of new data capture such as LiDar and laser scanning devices to collect information for construction or maintenance operations, and new methods to identify key elements to be avoided or included in the road design. Additionally, manuscripts are encouraged that describe new technologies for the improvement of construction practices that lead to economic and environmental gains for forest roads constructions, including road drainage structures.  

Another area to be considered is the integrated design of harvesting and roading systems to optimize the total extraction costs from forests. We are especially interested in how tethered logging will influence road spacing problems.  

Prof. Dr. Kevin Boston
Guest Editor

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

  • forest roads
  • LiDar
  • operations planning
  • forest transportation optimization

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Published Papers (2 papers)

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Research

10 pages, 1247 KiB  
Article
Prediction of Road Transport of Wood in Uruguay: Approach with Machine Learning
by Rodrigo Oliveira Almeida, Rafaele Almeida Munis, Diego Aparecido Camargo, Thamires da Silva, Valier Augusto Sasso Júnior and Danilo Simões
Forests 2022, 13(10), 1737; https://doi.org/10.3390/f13101737 - 20 Oct 2022
Cited by 6 | Viewed by 1926
Abstract
Among the activities that burden capital in the supply chain of forest-based industries, the activity of road transport of wood deserves to be highlighted. Machine learning techniques are applied the knowledge extracted from real data, and support strategies that aim to maximize the [...] Read more.
Among the activities that burden capital in the supply chain of forest-based industries, the activity of road transport of wood deserves to be highlighted. Machine learning techniques are applied the knowledge extracted from real data, and support strategies that aim to maximize the resources destined for it. Based on variables inherent to the wood transport activity, we verified whether machine learning models can act as predictors of the volume of wood to be transported and support strategic decision-making. The database came from companies in the pulp and paper segments, which totaled 26,761 data instances. After the data wrangling process, machine learning algorithms were used to build models, which were optimized from the hyperparameter adjustment and selected to compose the blended learning hierarchy. In addition to belonging to different methodological basis, a CatBoost Regressor, Decision Tree Regressor, and K Neighbors Regressor were selected mainly for providing minimal values to errors metrics and maximal values to determination coefficient. The learning by stack stands out, with a coefficient of determination of 0.70 and an average absolute percentage error of 6% in the estimation of the volume of wood to be transported. Based on variables inherent to the wood transport process, we verified that machine learning models can act in the prediction of the volume of wood to be transported and support strategic decision-making. Full article
(This article belongs to the Special Issue Forest Operations and Forest Road Networks Design)
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13 pages, 1760 KiB  
Article
Optimal Forest Road Density as Decision-Making Factor in Wood Extraction
by Danilo Simões, Felipe Soares Cavalcante, Roldão Carlos Andrade Lima, Qüinny Soares Rocha, Gilberto Pereira and Ricardo Hideaki Miyajima
Forests 2022, 13(10), 1703; https://doi.org/10.3390/f13101703 - 16 Oct 2022
Cited by 4 | Viewed by 2199
Abstract
Forest road construction projects mainly depend on factors related to terrain physiography, watershed, and wood harvesting. In the whole tree system, wood extraction is the activity most impacted by the density of forest roads, influencing the extraction distance. One of the alternatives is [...] Read more.
Forest road construction projects mainly depend on factors related to terrain physiography, watershed, and wood harvesting. In the whole tree system, wood extraction is the activity most impacted by the density of forest roads, influencing the extraction distance. One of the alternatives is the optimal forest road density approach, which allows for the minimization of wood extraction costs and the optimization of the productive area. Given the above, the objective of this study was to analyze whether the optimal forest road density in areas of forests planted with eucalyptus allows for maximum productivity and the lowest cost of the road-wood extraction binomial in a whole tree system. The technical and economic analysis of wood extraction was based on the study of time, operational efficiency, productivity, and the cost of wood extraction with a grapple skidder. For the optimal forest road density, the cost of the wood extraction activity was considered, as well as the cost of construction, reconstruction, and maintenance of roads. In addition, the cost of a loss of productive area and the cost of excess forest roads were weighted. The optimal forest road density was 30.49 m ha−1 for an average extraction distance of 81.99 m, with the cost of loss of productive area of 0.49 USD m³ and the excess road of 80.19 m, which represented a cost of 978.31 USD ha−1. It is concluded that the optimal forest road density allows for the identification of excess forest roads, allowing for a reduction in the total cost for the implementation of roads. Therefore, it can be considered an essential variable in the planning of the forest road network, providing improvements in productivity and the costs of wood extraction with a grapple skidder. Full article
(This article belongs to the Special Issue Forest Operations and Forest Road Networks Design)
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