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Articles containing the keyword 'value of information'

Category : Research article

article id 10089, category Research article
Arto Haara, Annika Kangas, Sakari Tuominen. (2019). Economic losses caused by tree species proportions and site type errors in forest management planning. Silva Fennica vol. 53 no. 2 article id 10089. https://doi.org/10.14214/sf.10089
Keywords: forest inventory; value of information; uncertainty; sub-optimality loss
Highlights: Errors in tree species proportions caused more economic losses for forest owners than site type errors; Economic losses due to sub-optimal treatments were observed from 26.5% to 31.7% of plots, depending on the remote sensing data set used; Even with the most accurate remote sensing data set, namely ALS data set, NPV losses were on average 124.4 € ha–1 with 3% interest rate.
Abstract | Full text in HTML | Full text in PDF | Author Info

The aim of this study was to estimate economic losses, which are caused by forest inventory errors of tree species proportions and site types. Our study data consisted of ground truth data and four sets of erroneous tree species proportions. They reflect the accuracy of tree species proportions in four remote sensing data sets, namely 1) airborne laser scanning (ALS) with 2D aerial image, 2) 2D aerial image, 3) 3D and 2D aerial image data together and 4) satellite data. Furthermore, our study data consisted of one simulated site type data set. We used the erroneous tree species proportions to optimise the timing of forest harvests and compared that to the true optimum obtained with ground truth data. According to the results, the mean losses of Net Present Value (NPV) because of erroneous tree species proportions at an interest rate of 3% varied from 124.4 € ha–1 to 167.7 € ha–1. The smallest losses were observed using tree species proportions predicted using ALS data and largest using satellite data. In those stands, respectively, in which tree species proportion errors actually caused economic losses, they were 468 € ha–1 on average with tree species proportions based on ALS data. In turn, site type errors caused only small losses. Based on this study, accurate tree species identification seems to be very important with respect to operational forest inventory.

  • Haara, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: arto.haara@luke.fi (email)
  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland ORCID https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
  • Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 2, FI-00791 Helsinki, Finland ORCID https://orcid.org/0000-0001-5429-3433 E-mail: sakari.tuominen@luke.fi
article id 9923, category Research article
Annika Kangas, Terje Gobakken, Stefano Puliti, Marius Hauglin, Erik Naesset. (2018). Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making. Silva Fennica vol. 52 no. 1 article id 9923. https://doi.org/10.14214/sf.9923
Keywords: forest inventory; value of information; uncertainty; remote sensing; cost-plus-loss; data quality
Highlights: Airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) are nearly equally valuable for harvest scheduling decisions even though ALS data is more precise; Large underestimates of stand volume are most dangerous errors for forest owner because of missed cutting probabilities; Relative RMSE of stand volume and the mean volume in a test area explain 77% of the variation between the expected losses due to errors in the data in the published studies; Increasing the relative RMSE of volume by 1 unit, increased the losses in average by 4.4 € ha–1.
Abstract | Full text in HTML | Full text in PDF | Author Info

Airborne laser scanning (ALS) has been the main method for acquiring data for forest management planning in Finland and Norway in the last decade. Recently, digital aerial photogrammetry (DAP) has provided an interesting alternative, as the accuracy of stand-based estimates has been quite close to that of ALS while the costs are markedly smaller. Thus, it is important to know if the better accuracy of ALS is worth the higher costs for forest owners. In many recent studies, the value of forest inventory information in the harvest scheduling has been examined, for instance through cost-plus-loss analysis. Cost-plus-loss means that the quality of the data is accounted for in monetary terms through calculating the losses due to errors in the data in the forest management planning context. These costs are added to the inventory costs. In the current study, we compared the losses of ALS and DAP at plot level. According to the results, the data produced using DAP are as good as data produced using ALS from a decision making point of view, even though ALS is slightly more accurate. ALS is better than DAP only if the data will be used for more than 15 years before acquiring new data, and even then the difference is quite small. Thus, the increased errors in DAP do not significantly affect the results from a decision making point of view, and ALS and DAP data can be equally well recommended to the forest owners for management planning. The decision of which data to acquire, can thus be made based on the availability of the data on first hand and the costs of acquiring it on the second hand.

  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80170 Joensuu, Finland E-mail: annika.kangas@luke.fi (email)
  • 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
  • Puliti, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: stefano.puliti@nibio.no
  • Hauglin, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: marius.hauglin@nmbu.no
  • Naesset, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: erik.naesset@nmbu.no
article id 55, category Research article
Antti Mäkinen, Annika Kangas, Mikko Nurmi. (2012). Using cost-plus-loss analysis to define optimal forest inventory interval and forest inventory accuracy. Silva Fennica vol. 46 no. 2 article id 55. https://doi.org/10.14214/sf.55
Keywords: value of information; prediction error; inventory error
Abstract | View details | Full text in PDF | Author Info
In recent years, optimal inventory accuracy has been analyzed with a cost-plus-loss methodology, where the total costs of inventory include both the measurement costs and the losses from the decisions based on the collected information. Losses occur, when the inaccuracies in the data lead to sub-optimal decisions. In almost all cases, it has been assumed that the accuracy of the once collected data remains the same throughout the planning period, and the period has been from 10 up to 100 years. In reality, the quality of the data deteriorates in time, due to errors in the predicted growth. In this study, we carried out a cost-plus-loss analysis accounting for the errors in (stand-level) growth predictions of basal area and dominant height. In addition, we included the inventory errors of these two variables with several different levels of accuracy, and costs of inventory with several different assumptions of cost structure. Using the methodology presented in this study, we could calculate the optimal inventory interval (life-span of data) minimizing the total costs of inventory and losses through the 30-year planning period. When the inventory costs only to a small extent depended on the accuracy, the optimal inventory period was 5 years and optimal accuracy RMSE 0%. When the costs more and more heavily depended on the accuracy, the optimal interval turned out to be either 10 or 15 years, and the optimal accuracy reduced from RMSE 0% to RMSE 20%. By increasing the accuracy of the growth models, it was possible to reduce the inventory accuracy or lengthen the interval, i.e. obtain clear savings in inventory costs.
  • Mäkinen, Simosol Oy, Rautatietori 4, FI-11130 Riihimäki, Finland E-mail: antti.makinen@simosol.fi (email)
  • Kangas, University of Helsinki, Department of Forest Sciences, Helsinki, Finland E-mail: ak@nn.fi
  • Nurmi, University of Helsinki, Department of Forest Sciences, Helsinki, Finland E-mail: mn@nn.fi
article id 525, category Research article
Thomas Knoke. (2002). Value of complete information on red heartwood formation in beech (Fagus sylvatica). Silva Fennica vol. 36 no. 4 article id 525. https://doi.org/10.14214/sf.525
Keywords: value of information; economics of beech; red heartwood; silvicultural treatment
Abstract | View details | Full text in PDF | Author Info
Beech (Fagus sylvatica L.) is the most important deciduous tree species in Germany. The wood of beech shows normally a bright colour (white beech) as long as no coloured heartwood has been formed. The facultative heartwood formation is induced when oxygen enters central parts of older trees, where dead or at least less vital parenchyma exist. The coloured heartwood is usually called ‘red heartwood’. Beech without red heartwood can preferably be found in younger trees which show a high water content even in central parts of the stem. The presence of red heartwood is regarded as a severe reduction of timber quality. Numerous studies have investigated opportunities to derive information on the presence and characteristics of red heartwood of standing beech trees. But until now it has not been tested whether such information could be helpful to improve the economics of beech-silviculture. This paper investigates whether complete information on the heartwood of standing beech could be useful to control the proportion of discoloured timber harvested during one rotation. It is also examined, which kind of information on the heartwood could be used to improve the economic results. To verify this, simulations based on simple algorithms were conducted. The general assumption was made that all information on the heartwood would be available. The results show that information which is restricted on the mere existence of red heartwood is neither suited to significantly reduce the amount of coloured timber nor is it possible to improve economic results based on this information. Only based on information on the recent formation of red heartwood of beech, which is actually still white the amount of discoloured timber can be reduced significantly. Consequently the discounted cash flows can only be substantially improved based on information on an expected formation of recent red heartwood.
  • Knoke, Institute of Silviculture and Forest Management, Technische Universität München, Am Hochanger 13, D-85354 Freising, Germany E-mail: knoke@wbfe.forst.tu-muenchen.de (email)

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