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Articles containing the keyword 'probability'

Category : Article

article id 5547, category Article

Tiina Tolvanen-Sikanen, Pertti Harstela, Lauri Sikanen. (1995). A game theoretic simulation model for quality oriented timber supply to sawmills. Silva Fennica vol. 29 no. 1 article id 5547. https://doi.org/10.14214/sf.a9198

Keywords: simulation; quality; timber procurement; supply; sawmills; statistical analysis; probability

Abstract | View details | Full text in PDF | Author Info

The first aim of this study was to develop a simulation model describing the flow of different timber qualities to different firms. The second aim was to study preliminary the factors which affect timber distributions. In addition, we tested the hypothesis that in a small sawmill firm the traditional way of organizing timber procurement does not direct effectively good quality logs to the special production. The game theoretic approaching and the principles of Monte-Carlo simulation were applied in development of the simulation model. The most important factors of the model were tried to find for further studies with sensitive analysis. Empirical validation brought forth promising results in the area of one municipality. The buyer’s awareness of a marked stand, the seller’s willingness to sell a marked stand, the buyer’s ability to pay for wood and the proportion of first quality pine logs in a marked stand affected the distribution of pine logs. The results also supported the hypothesis that the traditional system, in which sawmills or their own forest departments procure themselves all timber needed, is not the most effective way to direct enough good quality timber to the special production.

Tolvanen-Sikanen, E-mail: tt@mm.unknown
Harstela, E-mail: ph@mm.unknown
Sikanen, E-mail: ls@mm.unknown

Category : Research article

article id 9918, category Research article

Ari Nikula, Vesa Nivala, Juho Matala, Kari Heliövaara. (2019). Modelling the effect of habitat composition and roads on the occurrence and number of moose damage at multiple scales. Silva Fennica vol. 53 no. 1 article id 9918. https://doi.org/10.14214/sf.9918

Keywords: forestry; Alces alces; damage probability; forest damage; forest plantation; habitat selection; habitat modelling; zero-inflated negative binomial distribution

Highlights: The occurrence and number of moose damage were modelled with a zero-inflated count model; An admixture of mature forests within plantations increased the number of damage; Vicinity of inhabited areas and roads reduced damage; Plantations in landscapes with a large amount of pine-dominated thinning forests had less damage in Lapland; Damage risk assessment should include characteristics specific to each region.

Abstract | Full text in HTML | Full text in PDF | Author Info

We modelled the effect of habitat composition and roads on the number and occurrence of moose (Alces alces L.) damage in Ostrobothnia and Lapland using a zero-inflated count model. Models were developed for 1 km², 25 km² and 100 km² landscapes consisting of equilateral rectangular grid cells. Count models predict the number of damage, i.e. the number of plantations and zero models the probability of a landscape being without damage for a given habitat composition. The number of moose damage in neighboring grid cells was a significant predictor in all models. The proportion of mature forest was the most frequent significant variable, and an increasing admixture of mature forests among plantations increased the number and occurrence of damage. The amount of all types of plantations was the second most common significant variable predicting increasing damage along with increasing amount of plantations. An increase in thinning forests as an admixture also increased damage in 1 km² landscapes in both areas, whereas an increase in pine-dominated thinning forests in Lapland reduced the number of damage in 25 km² landscapes. An increasing amount of inhabited areas in Ostrobothnia and the length of connecting roads in Lapland reduced the number of damage in 1 and 25 km² landscapes. Differences in model variables between areas suggest that models of moose damage risk should be adjusted according to characteristics that are specific to the study area.

Nikula, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: ari.nikula@luke.fi
Nivala, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: vesa.nivala@luke.fi
Matala, Natural Resources Institute Finland (Luke), Natural resources, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: juho.matala@luke.fi
Heliövaara, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: kari.heliovaara@helsinki.fi

article id 975, category Research article

Renats Trubins, Ola Sallnäs. (2014). Categorical mapping from estimates of continuous forest attributes – classification and accuracy. Silva Fennica vol. 48 no. 2 article id 975. https://doi.org/10.14214/sf.975

Keywords: Sweden; land cover maps; forest type maps; map accuracy assessment; class membership probability; Bayesian network; k-NN estimates

Highlights: The paper presents an approach to classification and accuracy assessment of ad-hoc categorical maps based on existing spatial datasets with estimates of continuous forest variables; Pixel level class membership probabilities are estimated using a Bayesian network model.

Abstract | Full text in HTML | Full text in PDF | Author Info

Spatially explicit data on forest attributes is demanded for various research with landscape perspective. Existing datasets with estimates of continuous forest variables are often used as the basis for producing categorical forest type maps. Normally, this type of maps are used without knowing their accuracy. This paper presents a Bayesian network model for estimating pixel level class membership probabilities of thus derived categorical maps. Class membership probabilities can be used as a post-classification measure of map accuracy and in the process of map classification affecting the assignments of class labels. The method is applied in mapping deciduous dominated forests on the basis of the k-NN Sweden 2005 dataset in a study area in southern Sweden. The results indicate rather low accuracy for deciduous class regardless of the map classification method: 0.48 versus 0.50 in the maps classified without and with the use of the class membership probabilities given equal deciduous area. When probability-based classification is applied, the level of accuracy varies with the assumed map class proportions. Thus, when deciduous class area corresponding to the National Forest Inventory estimate was used, the accuracy of only 0.35 was obtained for the deciduous map class.

Trubins, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 230 53 Alnarp, Sweden E-mail: renats.trubins@slu.se
Sallnäs, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 230 53 Alnarp, Sweden E-mail: ola.sallnas@slu.se

article id 376, category Research article

Nils Lexerød, Trond Eid. (2005). Recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway. Silva Fennica vol. 39 no. 3 article id 376. https://doi.org/10.14214/sf.376

Keywords: regeneration; national forest inventories; growth simulators; probability models; conditional models; Norway

Abstract | View details | Full text in PDF | Author Info

The objective of the present study was to develop recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway. The models were developed from permanent sample plots established by the National Forest Inventory, and they will be included in a growth simulator that is part of a large-scale forestry scenario model. The modelling was therefore restricted to independent variables directly or indirectly available from inventories for practical forest management planning. A two-stage modelling approach that suited the stochastic nature of recruitment in boreal forests was used. Models predicting the probability of recruitment were estimated in a first stage, and conditional models for the number of recruits were developed in a second. The probability models as well as the conditional models were biologically realistic and logical. The goodness of fit tests revealed that the probability models fitted the data well, while the coefficients of determination for the conditional models were relatively low. No independent test data were available, but comparisons of predicted and observed number of recruits in different sub-groups of the data revealed few large deviations. The high level of large random errors was probably due to the great variability observed in number of recruits rather than inappropriate specifications of the models. Provided the generally high level of uncertainty connected to analysis performed with large-scale forestry scenario models and the stochastic nature of recruitment, the presented models seem to give satisfactory levels of accuracy.

Lexerød, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail: nils.lexerod@umb.no
Eid, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway. E-mail nils.lexerod@umb.no E-mail: te@nn.no

article id 384, category Research article

Jorge Cancino, Joachim Saborowski. (2005). Comparison of randomized branch sampling with and without replacement at the first stage. Silva Fennica vol. 39 no. 2 article id 384. https://doi.org/10.14214/sf.384

Keywords: Randomized Branch Sampling; sampling without replacement; probability proportional to size; unequal selection probabilities; multistage sampling

Abstract | View details | Full text in PDF | Author Info

Randomized Branch Sampling (RBS) is a multistage sampling procedure using natural branching in order to select samples for the estimation of tree characteristics. Usually, sampling units are selected with unequal probabilities. Conventional RBS uses sampling with replacement (SWR) for repeated sampling on the first stage, and the sample size equals 1 on all subsequent stages, thus resulting in n so-called sample paths. When the sampling fraction is large multiple selections of first stage units are likely. Sampling without replacement (SWOR) at the first stage is an alternative that is expected to increase efficiency of the procedure. In this case, the second stage sample size m must be larger than 1 to enable unbiased variance estimation. In the present study, a theoretical and an empirical comparison of the conventional RBS and the SWOR variant was accomplished. Requiring a certain precision of the RBS estimation, the conventional RBS method is mostly more time-consuming than the variant with SWOR at the first stage. Only if m = 1 is chosen as second stage sample size for the SWOR RBS, this is often more time-consuming. In those cases, conventional RBS is up to 5% cheaper. In general, the larger m is, the more expensive is conventional RBS compared with the variant with swor at the first stage. The smaller the ratio of the variance between the primary units to the total variance of the estimate, the larger is the advantage of the SWOR variant. Generally, it can be shown that the gain of efficiency by SWOR is larger in case of weak correlations between auxiliary and target variable.

Cancino, Facultad de Ciencias Forestales, Universidad de Concepción, Chile E-mail: jcancino@udec.cl
Saborowski, Institut für Forstliche Biometrie und Informatik, Georg-August-Universität Göttingen, Germany E-mail: js@nn.de

article id 637, category Research article

Hirofumi Kuboyama, Hiroyasu Oka. (2000). Climate risks and age-related damage probabilities – effects on the economically optimal rotation length for forest stand management in Japan. Silva Fennica vol. 34 no. 2 article id 637. https://doi.org/10.14214/sf.637

Keywords: simulation; climatic risks; damage probability; age class; optimal rotation period; land expectation value

Abstract | View details | Full text in PDF | Author Info

We estimated the damage probability according to age class and major climatic disasters based on ‘Statistical Yearbook of National Forest Insurance’ from 1960 to 1996. The probability of snow damage is high for young stands, then gradually decreases with age. On the other hand, the risk of wind damage gradually increases with age. Decisions about rotation age should be based on the distribution of damage probability with stand age. Risk of damage has two contradictory effects on the optimal rotation period; one is that the rotation-shortening effect caused by risk of damage around harvest age; another is the rotation-extending effect due to decrease of rent by the risk of damage through the raising period. Change of optimal rotation depends on the relative magnitude of these effects. We examine this by calculating land expectation value (LEV) using a simulation model with the empirical damage probability, price and cost. Change of the optimal rotation period obtained from the national average damage probability is not significant. However, the optimal rotation is shorter in high wind risk areas and is longer in high snow risk areas. It is because the damage probability for a mature stand is high in the case of wind and low in the case of snow. In addition, the extent of decrease in LEV is smaller for wind than for snow. The results of simulation based on empirical data confirm that the optimal rotation period can become either shorter or longer through incorporating risk in decision making, depending on the damage probability distribution with stand age.

Kuboyama, Forestry and Forest Products Research Institute Tohoku Center, Nabeyashiki 72, Shimo-Kuriyagawa, Morioka, Iwate, 020-0123 Japan E-mail: kuboyama@ffpri-thk.affrc.go.jp
Oka, Forestry and Forest Products Research Institute Tohoku Center, Nabeyashiki 72, Shimo-Kuriyagawa, Morioka, Iwate, 020-0123 Japan E-mail: ho@nn.jp

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