Articles containing the keyword 'harvester'

• Noordermeer, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0002-8840-0345 E-mail: lennart.noordermeer@nmbu.no
• Ørka, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0002-7492-8608 E-mail: hans-ole.orka@nmbu.no
• Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: terje.gobakken@nmbu.no

Newly developed positioning systems in cut-to-length harvesters enable georeferencing of individual trees with submeter accuracy. Together with detailed tree measurements recorded during processing of the tree, georeferenced harvester data are emerging as a valuable tool for forest inventory. Previous studies have shown that harvester data can be linked to airborne laser scanner (ALS) data to estimate a range of forest attributes. However, there is little empirical evidence of the benefits of improved positioning accuracy of harvester data. The two objectives of this study were to (1) assess the accuracy of timber volume estimation using harvester data and ALS data acquired with different scanners over multiple years and (2) assess how harvester positioning errors affect merchantable timber volume predicted and estimated from ALS data. We used harvester data from 33 commercial logging operations, comprising 93 731 harvested stems georeferenced with sub-meter accuracy, as plot-level training data in an enhanced area-based inventory approach. By randomly altering the tree positions in Monte Carlo simulations, we assessed how prediction and estimation errors were influenced by different combinations of simulated positioning errors and grid cell sizes. We simulated positioning errors of 1, 2, …, 15 m and used grid cells of 100, 200, 300 and 400 m². Values of root mean square errors obtained for cell-level predictions of timber volume differed significantly for the different grid cell sizes. The use of larger grid cells resulted in a greater accuracy of timber volume predictions, which were also less affected by positioning errors. Accuracies of timber volume estimates at logging operation level decreased significantly with increasing levels of positioning error. The results highlight the benefit of accurate positioning of harvester data in forest inventory applications. Further, the results indicate that when estimating timber volume from ALS data and inaccurately positioned harvester data, larger grid cells are beneficial.

• Noordermeer, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: lennart.noordermeer@nmbu.no
• Næsset, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: erik.naesset@nmbu.no
• Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: terje.gobakken@nmbu.no

The effect of harvester operator tree selection or prior tree marking in thinning operations on satisfactory results and performance has been widely discussed. In harvester operator tree selection, the machine operator decides on the fly which trees are selected to remain or cut. The objective of the study was to analyze the effect of prior tree marking, thinning method and topping diameter on harvester performance in low-diameter thinning operations. The entire thinning operation was captured using video technology. Overall, 2.36 ha divided into 48 plots with 5202 trees were thinned with an average diameter at breast height (dbh) over bark for all plots of between 12.5 and 14.7 cm. In total, 3122 trees were harvested, resulting in 60% removal of stem number over all plots. The harvester achieved a mean productivity of 7.38 m³ PMH₀^–1 with 1.48 m³ PMH₀^–1 SEM, with stem volume having the major influence on harvesting productivity. Prior tree marking, topping and thinning method did not significantly affect productivity. Without prior tree marking by the foresters, harvesting removal was shifted toward lower diameters. Within the unmarked plots, 7.0% of the residual trees were damaged compared with 3.2% in marked plots.

• Holzleitner, University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan-Straße 82/3, A-1190 Vienna, Austria https://orcid.org/0000-0001-8489-3050 E-mail: franz.holzleitner@boku.ac.at
• Langmaier, University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Silviculture, Peter-Jordan-Straße 82/3, A-1190 Vienna, Austria; Austrian Research Centre for Forests, Department of Forest Growth and Silviculture, Seckendorff Gudent Weg 8, A-1130 Vienna, Austria E-mail: magdalena.langmaier@bfw.gv.at
• Hochbichler, University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Silviculture, Peter-Jordan-Straße 82/3, A-1190 Vienna, Austria E-mail: eduard.hochbichler@boku.ac.at
• Obermayer, University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan-Straße 82/3, A-1190 Vienna, Austria; Agricultural Technical School of Pyhra, Kyrnbergstraße 4, A-3143 Pyhra, Austria E-mail: bernhardt.obermayer@lfs-pyhra.ac.at
• Stampfer, University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan-Straße 82/3, A-1190 Vienna, Austria http://orcid.org/0000-0001-9350-2859 E-mail: karl.stampfer@boku.ac.at
• Kanzian, University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan-Straße 82/3, A-1190 Vienna, Austria http://orcid.org/0000-0002-1198-9788 E-mail: christian.kanzian@boku.ac.at

Accurately positioned single-tree data obtained from a cut-to-length harvester were used as training harvester plot data for k-nearest neighbor (k-nn) stem diameter distribution modelling applying airborne laser scanning (ALS) information as predictor variables. Part of the same harvester data were also used for stand-level validation where the validation units were stands including all the harvester plots on a systematic grid located within each individual stand. In the validation all harvester plots within a stand and also the neighboring stands located closer than 200 m were excluded from the training data when predicting for plots of a particular stand. We further compared different training harvester plot sizes, namely 200 m², 400 m², 900 m² and 1600 m². Due to this setup the number of considered stands and the areas within the stands varied between the different harvester plot sizes. Our data were from final fellings in Akershus County in Norway and consisted of altogether 47 stands dominated by Norway spruce. We also had ALS data from the area. We concentrated on estimating characteristics of Norway spruce but due to the k-nn approach, species-wise estimates and stand totals as a sum over species were considered as well. The results showed that in the most accurate cases stand-level merchantable total volume could be estimated with RMSE values smaller than 9% of the mean. This value can be considered as highly accurate. Also the fit of the stem diameter distribution assessed by a variant of Reynold’s error index showed values smaller than 0.2 which are superior to those found in the previous studies. The differences between harvester plot sizes were generally small, showing most accurate results for the training harvester plot sizes 200 m² and 400 m².

• Maltamo, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu E-mail: matti.maltamo@uef.fi
• Hauglin, Norwegian Institute of Bioeconomy Research, Division of Forest and Forest Resources, P.O. Box 115, 1431 Ås, Norway E-mail: marius.hauglin@nibio.no
• Naesset, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, 1432 Ås, Norway E-mail: erik.naesset@nmbu.no
• Gobakken, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, 1432 Ås, Norway E-mail: terje.gobakken@nmbu.no

Tree bucking, defined as the process in which a stem is segmented into shorter logs of varying lengths, has a significant effect on the value adding potential of a forest enterprise. Because of its importance in terms of correct product and length combinations, improper bucking can lead to financial losses. In this study, two treatments (OFF: quality bucking performed by the operator while using hot keys and ON: automatic bucking using the optimized suggestions from the harvester on-board computer; OBC) were tested in a Norway spruce (Picea abies [L.] Karst.) dominated stand located in Germany. Both treatments had the aim to maximize the value of a stem. The research took place in an 80-year old spruce and beech stand under a regenerative cutting. Fully-mechanized harvesting was performed with an 8-wheel Ponsse Bear single-grip harvester equipped with a H8 harvesting head. Results indicated that the product recovery of the two treatments differed by 4% in undamaged trees (no broken tree-tops or stems) to the benefit of manual bucking. However, the revenue of trees subjected to optimized bucking were up to 4% higher (in average 3%) than those of the manual bucking once expressed on a per cubic meter basis. Moreover, the harvesting productivity of the ON treatment was at the maximum 17% higher compared to the OFF treatment. Based on the results from this case study, the use of an optimization software in Norway spruce dominated stands with the aim to maximize the value of single stems showed promising results.

• Labelle, Assistant Professorship of Forest Operations, Department of Ecology and Ecosystem Management, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, D-85354 Freising, Germany E-mail: eric.labelle@tum.de
• Huß, Assistant Professorship of Forest Operations, Department of Ecology and Ecosystem Management, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, D-85354 Freising, Germany E-mail: linus.huss@gmx.de

Early thinnings are laborious and costly. Thus forest companies are searching for cost and time efficient ways to carry out this task. The study’s purpose was to determine the productivity of the EF28 accumulating energy wood harvesting head in harvesting small-diameter hornbeam (Carpinus betulus L.) undergrowth trees and evaluate the effect of its multi-tree handling (MTH) capacity on time consumption. The harvester was a wheeled, three-axle Komatsu 911. A time study of 7.1 hours on 19 plots, with a total area of 0.76 ha was conducted. On average, the harvested tree volume was 8 dm³ and the stand density was 2666 trees/ha. The productivity was modelled with MTH conduction, mean diameter at breast height and the number of trees handled per cycle as independent variables. On average, MTH took 27% longer per cycle, increased extracted volume per cycle by 33% and consequently increased productivity with 5.0%. In 71.9% of the cycles more than one tree was handled and if so, dimensions were smaller than in single-tree handling (5.8 cm vs. 12.0 cm). Maximum felling diameter of 23 cm was about 15% smaller than in softwood (according to the manufacturer’s specifications) and the driver didn’t exploit the EF28’s theoretical potential in terms of trees handled per cycle. It can be concluded that the head could significantly improve productivity in small-diameter wood procurement.

• Erber, Addresses University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan Straße 82/3, A-1190 Vienna, Austria E-mail: gernot.erber@boku.ac.at
• Holzleitner, Addresses University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan Straße 82/3, A-1190 Vienna, Austria E-mail: franz.holzleitner@boku.ac.at
• Kastner, Addresses University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan Straße 82/3, A-1190 Vienna, Austria E-mail: maximilian.kastner@boku.ac.at
• Stampfer, Addresses University of Natural Resources and Life Sciences Vienna, Department of Forest and Soil Sciences, Institute of Forest Engineering, Peter-Jordan Straße 82/3, A-1190 Vienna, Austria E-mail: karl.stampfer@boku.ac.at

• Szewczyk, University of Agriculture in Krakow, Faculty of Forestry, Institute of Forest Utilization and Forest Technology, Department of Forest and Wood Utilization, Al. 29-Listopada 46, 31-425 Krakow, Poland E-mail: rlszewcz@cyf-kr.edu.pl
• Sowa, University of Agriculture in Krakow, Faculty of Forestry, Institute of Forest Utilization and Forest Technology, Department of Forest and Wood Utilization, Al. 29-Listopada 46, 31-425 Krakow, Poland E-mail: rlsowa@cyf-kr.edu.pl
• Grzebieniowski, University of Agriculture in Krakow, Faculty of Forestry, Institute of Forest Utilization and Forest Technology, Department of Forest and Wood Utilization, Al. 29-Listopada 46, 31-425 Krakow, Poland E-mail: wrzoswj@interia.pl
• Kormanek, University of Agriculture in Krakow, Faculty of Forestry, Institute of Forest Utilization and Forest Technology, Department of Forest Work Mechanisation, Al. 29-Listopada 46, 31-425 Krakow, Poland E-mail: rlkorma@cyf-kr.edu.pl
• Kulak, University of Agriculture in Krakow, Faculty of Forestry, Institute of Forest Utilization and Forest Technology, Department of Forest and Wood Utilization, Al. 29-Listopada 46, 31-425 Krakow, Poland E-mail: rlkulak@cyf-kr.edu.pl
• Stańczykiewicz, University of Agriculture in Krakow, Faculty of Forestry, Institute of Forest Utilization and Forest Technology, Department of Forest and Wood Utilization, Al. 29-Listopada 46, 31-425 Krakow, Poland E-mail: rlstancz@cyf-kr.edu.pl

• Nuutinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: yrjo.nuutinen@metla.fi
• Väätäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kv@nn.fi
• Asikainen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: aa@nn.fi
• Prinz, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: rp@nn.fi
• Heinonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jh@nn.fi

• Nurminen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tuomo.nurminen@joensuu.fi
• Korpunen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: hk@nn.fi
• Uusitalo, Finnish Forest Research Institute, Parkano Research Unit, Kaironiementie 54, FI-39700 Parkano, Finland E-mail: ju@nn.fi

• Ovaskainen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: heikki.ovaskainen@joensuu.fi

• Andersson, Swedish University of Agricultural Sciences, Department of Silviculture, S-901 83 Umeå, Sweden E-mail: je@nn.se
• Eliasson, Swedish University of Agricultural Sciences, Department of Silviculture, S-901 83 Umeå, Sweden E-mail: lars.eliasson@ssko.slu.se

The productivity of cut-to-length machine operators exhibits a significant disparity, with the most productive individuals demonstrating twice the efficiency of their less productive counterparts. This discrepancy is largely attributed to variations in work methods. While supervised training has proven effective in streamlining work methods and enhancing productivity, the availability of forest-machine instructors for supervision is limited. Intelligent coaching systems (ICS) are periodically proposed to address this constraint. ICS are computer-based aids that offer machine operators real-time feedback on their work and guide them on how to rationalize their work. The successful implementation of ICS initially requires the development of systems for automatic work-element detection (AWED). Therefore, this article explores the history, current status, and technological possibilities of AWED. Additionally, key features of ICS are briefly reviewed. Lastly, a broader, interdisciplinary discussion is initiated on how to strategically allocate limited research resources. Questions surrounding the feasible ambition level for ICS and AWED are raised, prompting considerations for the next steps in research and development.

• Manner, Skogforsk, Uppsala Science Park, 751 83 Uppsala, Sweden https://orcid.org/0000-0002-4982-3855 E-mail: jussi.manner@skogforsk.se