Speaker
Description
Modern cut to length (CTL) harvesters increasingly incorporate positioning information as part of their standard data output. This information ranges from machine traces that continuously log machine movement, to base machine positioning during felling, to the positioning of stumps and, ultimately, each processed log. While high accuracy GNSS receivers with coordinate corrections can theoretically provide centimetre scale accuracy for base machine positioning, stump and log positioning require additional knowledge of boom tip location and head orientation—factors that introduce further uncertainty. Understanding the performance of these systems is important when developing practical use cases.
In late 2025, the Wood Value Trial 2025 was conducted north of Uppsala, Sweden, with the aim to assess the performance of modern CTL harvesters across several key categories, including measurement precision (length and diameter), bucking performance, incidence of timber damage, and the capability and accuracy of stem and log positioning. Seven manufacturers participated in the trial, Log Max, Ponsse, Logset, John Deere, Ecolog, Rottne and Komatsu. All harvesters provided base machine positioning during felling, three included functionality for stump positioning, and one supported log-positioning. Stump positioning were evaluated by comparing recorded stump coordinates with control measurements collected using a handheld GNSS receiver with centimetre scale accuracy. The same comparison method was applied to evaluate log center positioning. For the stump positioning a sample of 30 stumps were evaluated for each manufacturer while the evaluation of the log positions consisted of 22 logs.
Results showed average stump positioning errors ranging from 0.16 to 1.38 m, with standard deviations between 0.11 and 0.73 m. For log positioning, the average error was 0.42 m, with standard deviations of 0.45 m and 0.26 m along the principal axes.
As a demonstration of a practical application using positioning, the Vinnova funded DigForeTrace and Mista Digital Forest projects used log positioning to enable identification of individual logs by forwarders, allowing stem specific information gathered by the harvester to be connected to individual logs carried out to roadside locations. As the identities of logs were known so too were the harvester measurements and combined with industry gate data, logs could be matched to a reasonable subset of candidates using length and diameter attributes. This passive tracing method produced lists of suggested matches for each log, recovering 67–76% of logs with an average of 3–33 suggestions per log. Because each candidate’s unique harvester identifier is retained, the full suite of harvester recorded positioning data can be used to visualize where each log was cut and where each stem originally grew showcasing a use case for precise positioning information.
| Keywords | Positioning; StanForD2010; Tracability; WoodValueTrial |
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