Articles by Teijo Palander

Linear programming (LP) is an important method for allocation of wood inventory stock. It is, for instance, used alone in tactical planning systems, which currently are in wide use at the higher hierarchical level in the functionally decentralized planning of the Finnish forest industry. Unfortunately, LP as a solution method has not been capable of handling spatial data that seem to characterize planning systems in geographical decentralization. In the present study, GIS was used to assimilate data from different wood procurement functions, to calculate transportation distances and cost figures, and to write the data in ASCII files, which were then used as input for the LP model. Using the experiments and methods of GIS on a planning system developed according to participatory planning, the results of this study suggest that the participatory method was faster than the conventional LP method, when solved using actual data. The participatory method was also capable of providing the same global optimum for a wood allocation problem. The implications of these results for improving operational and tactical planning of wood procurement in Finland are discussed.

• Palander, E-mail: tp@mm.unknown

In southern Lapland, 70% of drained peatland forests have a peat layer thickness of less than one metre. On these sites, the question is how the subsoil under the peat affects groundwater level and thus timber harvesting. The aim of this study was to investigate the effect of the peat layer (<1 m) and subsoil on the groundwater level and its variation during the growing season (non-frost) by modelling the factors affecting water level. In sandy soils, the groundwater level rose by 20 cm when the peat layer thickness increased from 20 to 70 cm. In silty soils the effect of the peat thickness on groundwater remained minor. When the subsoil was sand or coarser, the groundwater level was usually deeper than when it was silty or finer. The effect of stand volume (m^–3 ha^–1) on the groundwater level was rather weak albeit significant. The model explained a significant part of the groundwater surface variation, with a marginal coefficient of determination (R²) of 68%. It seems that the rutting of roads could be avoided in late summer if the precipitation is remarkably lower during that period, or if the subsoil is sandy with thin peat layer on top of it. Because the groundwater level affects the load-bearing capacity of timber-harvesting machinery, it is important to study this issue in more detail in the future.

• Hiltunen, Lapland University of Applied Sciences, Jokiväylä 11, FI-96300 Rovaniemi, Finland E-mail: oivah@student.uef.fi
• Hallikainen, Natural Resources Institute Finland, Ounasjoentie 6, FI-96300 Rovaniemi, Finland E-mail: ville.hallikainen@luke.fi
• Palander, The University of Eastern Finland, Faculty of Science, Forestry and Technology, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-9284-5443 E-mail: teijo.s.palander@uef.fi

Road transport produces 90% of greenhouse gas emissions in timber transport in Finland. It is therefore necessary to understand the factors that affect driving speed, fuel consumption, and ultimately, emissions. The objective of this study was to assess the effect of road characteristics on timber truck driving speed and fuel consumption. Data from the fleet management and transport management systems of two timber trucks were collected over a year. A sample of 104 trips was drawn, and the tracking points were overlaid on the road data in a geographical information system. Thereafter, work phases were determined for the points, and they were visually classified into road and pavement classes. Subsequently, the data of 80 trips were utilised in regression analysis to further study the effects of the visually interpreted variables on driving speed and fuel consumption. Fuel consumption was explained by the proportion of forest roads and distance travelled with a loader, and the number of crossings and season when driving without a load. When driving with a load, both asphalt and gravel pavements decreased consumption, in contrast to an unpaved road. Crossings increased fuel consumption, as did the winter and spring months, and the total laden mass of the truck. In conclusion, the study showed that the functional Finnish road and pavement classes can be used to predict driving speed and fuel consumption.

• Anttila, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0002-6131-392X E-mail: perttu.anttila@luke.fi
• Ojala, UPM Metsä, Sirkkalantie 13 b, FI-80100 Joensuu, Finland E-mail: johannes.ojala@upm.com
• Palander, School of Forest Sciences, University of Eastern Finland (UEF), Yliopistokatu 7, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-9284-5443 E-mail: teijo.s.palander@uef.fi
• Väätäinen, Natural Resources Institute Finland (Luke), Yliopistokatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-6886-0432 E-mail: kari.vaatainen@luke.fi

• Oikari, Karelwood, Kontiolahti, Finland E-mail: markku.oikari@karelwood.com
• Kärhä, Metsäteho Oy, Helsinki, Finland E-mail: kk@nn.fi
• Palander, University of Eastern Finland, Faculty of Science and Forestry, Joensuu, Finland E-mail: tp@nn.fi
• Pajuoja, Metsäteho Oy, Helsinki, Finland E-mail: hp@nn.fi
• Ovaskainen, University of Eastern Finland, Faculty of Science and Forestry, Joensuu, Finland E-mail: ho@nn.fi

• Laukkanen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: sanna.laukkanen@joensuu.fi
• Palander, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tp@nn.fi
• Kangas, UPM-Kymmene Forest, P.O. Box 32, FI-37601 Valkeakoski, Finland E-mail: jk@nn.fi
• Kangas, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ak@nn.fi

• Palander, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: teijo.palander@joensuu.fi
• Turunen, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: kt@nn.fi
• Laukkanen, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: sl@nn.fi

• Palander, University of Joensuu, Faculty of Forestry, Box 111, FIN-80101 Joensuu, Finland E-mail: teijo.palander@forest.joensuu.fi
• Toivonen, University of Joensuu, Faculty of Forestry, Box 111, FIN-80101 Joensuu, Finland E-mail: mt@nn.fi
• Laukkanen, University of Joensuu, Faculty of Forestry, Box 111, FIN-80101 Joensuu, Finland E-mail: sl@nn.fi