Articles containing the keyword 'sawlog'

Totally 653 battens and planks sawn from butt logsof Scots pine (Pinus sylvestris L.) were chosen from 3 saw mills. The sawn goods were sorted according to normal sorting principles. In order to determine growth rate in the youth, the mean value of the average ring width was measured at the butt end at various distances from the pith.

The average ring width increased as the quality of the sawn goods decreased. The difference between the quality classes in ring width was measured between 2 and 4 cm from the pith. As the size of sawn goods, and, simultaneously, the log size increased, the average ring width increased in a given quality class. Research reinforced previous results, in which slow diameter growth of young Scots pines has been shown to reflect the good quality of sawn goods.

The PDF includes a summary in English.

• Halinen, E-mail: mh@mm.unknown

A test sawing was made of 807 Scots pine (Pinus sylvestris L.) saw logs of varying size and quality. The most important knot characteristic affecting the value of sawn goods was the diameter of the thickest dry knot. The new minimum requirements for pine logs were proposed on the basis of top diameter of the log and the diameter of the thickest dry and living knot.

The PDF includes a summary in English

• Kärkkäinen, E-mail: mk@mm.unknown
• Halinen, E-mail: mh@mm.unknown

The wages of logging and haulage has been dependent on the decisions of foremen. The aim of this study was to provide better insight on how working conditions in a logging site affect productivity of the work. Six working sites operated by Forest Service, Veitsiluoto Oy and Kemi Oy in the communes of Salla, Muonio and Kolari in Lapland were studied. The forests in the area were mostly Scots pine (Pinus sylvestris L.).

The effect of average volume of the stems, the average daily haulage over distances of various lengths, density of the stand and shape of the stem on effectivity was calculated. The size of the team was of considerable importance to the felling and haulage result in the Northern Finland where the feller assists in loading of the logs. One of the aims of the study was to find out what size of team is most advantageous for each haulage distance. The results show the optimum distance of haulage for teams of different sizes.

The article includes a summary in English.

• Maliniemi, E-mail: em@mm.unknown

The aim in the study was to compare alternatives for the prediction of factual sawlog volumes using airborne laser scanning (ALS) data in Scots pine (Pinus sylvestris L.) dominated forests in eastern Finland. Accurate estimates of factual sawlog volume are desirable to ease the planning of harvesting operations. The factual sawlog volume of pines was derived from visual bucking, i.e. a procedure where the defects were located on each stem during sample plot measurements. For other species, the theoretical sawlog volume was considered also as the factual sawlog volume due to data restrictions. We predicted factual sawlog volume with eight alternatives that were based on either linear mixed-effects models or k-nearest neighbour imputations. An existing sawlog reduction model, commonly used in Finland, was also tested individually and combined with a number of the alternatives, and site type information was also utilised. Model fitting and prediction was implemented at the 15 × 15 m level, but accuracy was assessed at the 30 × 30 m level. The relative root mean squared error (RMSE%) values for the factual sawlog volume predictions varied between 20.9% and 33.5%, and the best accuracy was obtained with a linear mixed-effects model. These results indicate that factual sawlog volumes in Scots pine dominated forests can be predicted with reasonable accuracy with ALS data.

• Karjalainen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tomikar@uef.fi
• Packalen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: petteri.packalen@uef.fi
• Räty, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: janne.raty@uef.fi
• Maltamo, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: matti.maltamo@uef.fi

Airborne laser scanning (ALS) data is nowadays often available for forest inventory purposes, but adequate field data for constructing new forest attribute models for each area may be lacking. Thus there is a need to study the transferability of existing ALS-based models among different inventory areas. The objective of our study was to apply ALS-based mixed models to estimate the diameter, height and crown base height of individual sawlog sized Scots pines (Pinus sylvestris L.) at three different inventory sites in eastern Finland. Different ALS sensors and acquisition parameters were used at each site. Multivariate mixed-effects models were fitted at one site and the models were validated at two independent test sites. Validation was carried out by applying the fixed parts of the mixed models as such, and by calibrating them using 1–3 sample trees per plot. The results showed that the relative RMSEs of the predictions were 1.2–6.5 percent points larger at the test sites compared to the training site. Systematic errors of 2.4–6.2 percent points also emerged at the test sites. However, both the RMSEs and the systematic errors decreased with calibration. The results showed that mixed-effects models of individual tree attributes can be successfully transferred and calibrated to other ALS inventory areas in a level of accuracy that appears suitable for practical applications.

• Korhonen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland http://orcid.org/0000-0002-9352-0114 E-mail: lauri.korhonen@uef.fi
• Repola, Natural Resources Institute of Finland (Luke), Natural resources, Eteläranta 55, FI-96300 Rovaniemi, Finland E-mail: jaakko.repola@luke.fi
• Karjalainen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tomikar@uef.fi
• Packalen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: petteri.packalen@uef.fi
• Maltamo, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: matti.maltamo@uef.fi

• Kolis, Aalto University, Department of Real Estate, Planning and Geoinformatics, P.O. Box 12200, FI-00076 Aalto, Finland E-mail: karin.kolis@aalto.fi
• Hiironen, Aalto University, Department of Real Estate, Planning and Geoinformatics, P.O. Box 12200, FI-00076 Aalto, Finland E-mail: juhana.hiironen@aalto.fi
• Ärölä, National Land Survey of Finland, Production Support Services, P.O. Box 84, FI-00521 Helsinki, Finland E-mail: esa.arola@nls.fi
• Vitikainen, Aalto University, Department of Real Estate, Planning and Geoinformatics, P.O. Box 12200, FI-00076 Aalto, Finland E-mail: arvo.vitikainen@aalto.fi