Jori Uusitalo, Zhu Mao, Son Cao, Omid Abdi. (2026). Assessing logging trail network performance using spatial configuration metrics. Silva Fennica vol. 60 no. 3 article id 26018. https://doi.org/10.14214/sf.26018

Keywords: silviculture; sustainable forest management; forest operations; timber harvesting; forest machines; GNSS positioning

Highlights: Proposes two complementary metrics – Coverage Coefficient and Structural Efficiency – to assess spatial arrangement performance of logging trail networks beyond traditional density measures; A new method is also introduced that computes geometrically meaningful mean spacing between adjacent trails, overcoming limitations of density-based approaches that may produce geometrically uneven trail distributions; Demonstrates how new metrics can be applied to data gathered from thinning operations in Central Finland; The new metrics support improved harvesting efficiency, automated trail planning, and sustainable forest management.

Abstract | Full text in HTML | Full text in PDF | Author Info

Logging trails are a critical component of modern forest harvesting operations, particularly in thinning and partial cutting, where trail layout strongly influences harvesting efficiency, soil disturbance, future stand growth, and carbon balance. Despite their importance, existing regulations and commonly used metrics – such as mean trail spacing and trail density – primarily address quantitative properties of logging trail networks and do not capture the qualitative aspects of network design. In this study, we introduce a novel concept for assessing the spatial arrangement performance of logging trail networks based on two complementary spatial configuration metrics: a Coverage Coefficient, describing the proportion of forest area reachable by harvesting machinery, and a Structural Efficiency Coefficient, comparing the actual trail length to an idealized network layout. Together, these metrics provide a geometrically meaningful and operationally relevant evaluation of trail network spatial arrangement beyond conventional density-based measures. We also introduce a method for computing a geometrically meaningful mean spacing between adjacent trails. The methodology is demonstrated using ten thinning sites from Central Finland. The results reveal clear differences in the spatial pattern of trail layouts among sites that are not detectable using traditional metrics alone. The proposed approach offers a practical tool for evaluating spatial arrangement performance of logging trail networks after harvesting, supporting operator feedback, regulatory assessment, and the development of automated trail network design and planning procedures. More broadly, the metrics provide a foundation for improving harvesting efficiency, reducing unnecessary trail density, and supporting environmentally sustainable forest management.

Uusitalo, Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland https://orcid.org/0000-0003-3793-1215 E-mail: jori.uusitalo@helsinki.fi
Mao, Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland https://orcid.org/0000-0002-8464-2558 E-mail: zhu.mao@helsinki.fi
Cao, Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland https://orcid.org/0009-0007-5285-7312 E-mail: caothaison@outlook.com.vn
Abdi, Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 University of Helsinki, Finland https://orcid.org/0000-0002-8048-8792 E-mail: omid.abdi@helsinki.fi

article id 25014, category Research article

Riku Tarvainen, Kirsi Riekki, Heikki Ovaskainen, Asko Poikela, Kalle Kärhä, Jukka Malinen. (2025). Estimating stand variables in first-thinnings using harvester data. Silva Fennica vol. 59 no. 3 article id 25014. https://doi.org/10.14214/sf.25014

Keywords: forest inventory; diameter distribution; stand variables; harvester data; accurate GNSS positioning; harvesting quality; Reynold’s error index

Highlights: The idea was to identify the trees removed from the strip roads from the harvester data and use them as a sample of the initial growing stock of the first thinning stand; The goal was also to estimate the number of stems, basal area and diameter distribution of the growing stock after thinning; The sampling method based on identifying strip road trees is applicable to monitoring the density of the remaining growing stock at first thinning stands.

Abstract | Full text in HTML | Full text in PDF | Author Info

First thinning is an important operation in forest management because it determines the further growth of the whole stand. Harvester operators open strip roads to the thinning stand and select which trees are removed and which are left to grow. Modern cut-to-length harvesters produce precise information about the dimensions and positions of the cut trees. The location of the harvester is already commonly recorded to harvester production (hpr) files, according to the StanForD 2010 standard, and recording the position of the harvester head is also becoming more common. The aim of this study was to develop a method to estimate the stem count and basal area of the remaining growing stock using this novel harvester data. Precision hpr data from Komatsu harvesters and reference field measurements were gathered from seven stands in western Finland in the summer of 2024. In the method used, the strip road trees were identified and used as samples representing the initial growing stock. The remaining growing stock was estimated using diameter distributions, and by subtracting the harvested trees from the initial growing stock. The results were evaluated using Reynold’s error index, in addition to a visual interpretation of the diameter distributions with respect to the reference data. We found that the method had the potential to determine the basal area and diameter distribution of the remaining growing stock. In the future, this method can be automated, which will allow automated reporting and quality management in first-thinning operations.

Tarvainen, Metsäteho Oy, Vernissakatu 1, FI-01300 Vantaa, Finland https://orcid.org/0009-0001-2336-3125 E-mail: riku.tarvainen@metsateho.fi
Riekki, Metsäteho Oy, Vernissakatu 1, FI-01300 Vantaa, Finland https://orcid.org/0009-0007-8366-3297 E-mail: kirsi.riekki@metsateho.fi
Ovaskainen, Metsäteho Oy, Vernissakatu 1, FI-01300 Vantaa, Finland https://orcid.org/0000-0001-5063-6662 E-mail: heikki.ovaskainen@metsateho.fi
Poikela, Metsäteho Oy, Vernissakatu 1, FI-01300 Vantaa, Finland E-mail: asko.poikela@metsateho.fi
Kärhä, University of Eastern Finland, School of Forest Sciences, Faculty of Science, Forestry and Technology, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: kalle.karha@uef.fi
Malinen, Metsäteho Oy, Vernissakatu 1, FI-01300 Vantaa, Finland https://orcid.org/0000-0002-5023-1056 E-mail: jukka.malinen@metsateho.fi

Click this link to register to Silva Fennica.

If you are a registered user, log in to save your selected articles for later access.

Contents alert

Your selected articles

Follow @SilvaFennica