Riku Tarvainen, Kirsi Riekki, Heikki Ovaskainen, Kalle Kärhä, Jukka Malinen. (2026). Strip-road tree identification and stand structure estimation using harvester data. Silva Fennica vol. 60 no. 3 article id 26021. https://doi.org/10.14214/sf.26021

Keywords: simulation; sampling; harvester data; accurate positioning

Highlights: Three methods for identifying strip-road trees from hpr data with accurate positioning were compared; Inner-stand spatial arrangement of trees and strip-road sampling sensitivity were quantified using theoretical strip-road layouts; Harvester-based strip-road sampling offers a practical and cost-efficient alternative for forest inventory, but estimates based solely on realised strip-road locations may be biased in certain stand conditions.

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

Harvester data are a potentially valuable source of detailed information on forest inventory in first-thinning stands. In first-thinning operations performed using modern cut-to-length harvesters, all the trees within the strip roads are removed. The resulting systematic strip road network covers approximately 15–20% of the stand area. We investigated how strip-road trees can be identified from harvested production data to quantify within-stand variation and evaluate how strip-road sample placement affects the representativeness of the sample. Three different strip-road tree identification methods were evaluated: (1) a boom-angle and -length method; (2) a buffer method using reconstructed strip-road centrelines in a global coordinate system; and (3) a boom-angle method. The accuracy of the resulting diameter distributions, stem counts and basal-area estimates was assessed using Reynold’s error index and root mean square error metrics against detailed field reference data. In addition, theoretical offset strip roads were established and systematically shifted across each measurement area to quantify within-stand variation and sampling sensitivity. The most accurate stem count estimates were obtained using the boom-angle and -length method and the buffer method, whereas the boom-angle sector method performed poorly. Offset strip-road tree samples revealed substantial variation in stem count and basal area in some stands, indicating that strip-road alignment and spatial heterogeneity can significantly influence the representativeness of the sample. Our findings show that, in general, harvester-based strip-road sampling is a feasible and cost-efficient approach for estimating stand-level forest variables in first thinnings if tree identification methods and spatial biases are carefully considered.

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.ovaskainen1@gmail.com
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

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

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