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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles containing the keyword 'ramet'.

Category: Research article

article id 9972, category Research article
Jukka Malinen, Harri Kilpeläinen, Erkki Verkasalo. (2018). Validating the predicted saw log and pulpwood proportions and gross value of Scots pine and Norway spruce harvest at stand level by Most Similar Neighbour analyses and a stem quality database. Silva Fennica vol. 52 no. 4 article id 9972. https://doi.org/10.14214/sf.9972
Highlights: Non-parametric prediction together with external stem quality database provides predictions usable for pre-harvest assessment at a stand level; The prediction of Norway spruce assortment recovery and value proved to be more accurate than the predictions for Scots pine; RMSE and bias of unit prices were 3.50 € m–3 and 0.58 € m–3 for pine and 2.60 € m–3 and 0.35 € m–3 for spruce.

Detailed pre-harvest information about the volumes and properties of growing stocks is needed for increased precision in wood procurement planning for just-in-time wood deliveries by cut-to-length (CTL) harvesters. In the study, the non-parametric Most Similar Neighbour (MSN) methodology was evaluated for predicting external quality of Scots pine and Norway spruce, expressed as stem sections fulfilling the saw log dimension and quality requirements of Finnish forest industry, as they affect the recovery of timber assortments and the value of a pre-harvest stand. Effects of external tree quality were evaluated using saw log recovery and saw log reduction caused by stem defects, as well as total timber value (€) and average unit value (€ m–3) in a stand. Root mean square error (RMSE) of saw log recovery and reduction were 9.12 percentile points (pp) for Scots pine and 6.38 pp for Norway spruce stands. In the unit value considerations, the predictions compared with measurements resulted in the RMSE of 3.50 € m–3 and the bias of 0.58 € m–3 in Scots pine stands and 2.60 € m–3, and 0.35 € m–3 in Norway spruce stands, respectively. The presented MSN based approach together with the utilization of the external stem quality database included in the ARVO software could provide dimension and external quality predictions usable for pre-harvest assessment of timber stock at a stand level. This prediction methodology is usable especially in analyses where timber assortment recoveries, values and unit prices are compared when different bucking objectives are used.

  • Malinen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: jukka.malinen@uef.fi (email)
  • Kilpeläinen, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland ORCID ID:E-mail: harri.kilpelainen@luke.fi
  • Verkasalo, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland ORCID ID:E-mail: erkki.verkasalo@luke.fi
article id 1568, category Research article
Jouni Siipilehto, Harri Lindeman, Mikko Vastaranta, Xiaowei Yu, Jori Uusitalo. (2016). Reliability of the predicted stand structure for clear-cut stands using optional methods: airborne laser scanning-based methods, smartphone-based forest inventory application Trestima and pre-harvest measurement tool EMO. Silva Fennica vol. 50 no. 3 article id 1568. https://doi.org/10.14214/sf.1568
Highlights: An airborne laser scanning grid-based approach for determining stand structure enabled bi- or multimodal predicted distributions that fitted well to the ground-truth harvester data; EMO and Trestima applications needed stand-specific inventory for sample measurements or sample photos, respectively, and at their best, provided superior accuracy for predicting certain stand characteristics.

Accurate timber assortment information is required before cuttings to optimize wood allocation and logging activities. Timber assortments can be derived from diameter-height distribution that is most often predicted from the stand characteristics provided by forest inventory. The aim of this study was to assess and compare the accuracy of three different pre-harvest inventory methods in predicting the structure of mainly Scots pine-dominated, clear-cut stands. The investigated methods were an area-based approach (ABA) based on airborne laser scanning data, the smartphone-based forest inventory Trestima app and the more conventional pre-harvest inventory method called EMO. The estimates of diameter-height distributions based on each method were compared to accurate tree taper data measured and registered by the harvester’s measurement systems during the final cut. According to our results, grid-level ABA and Trestima were generally the most accurate methods for predicting diameter-height distribution. ABA provides predictions for systematic 16 m × 16 m grids from which stand-wise characteristics are aggregated. In order to enable multimodal stand-wise distributions, distributions must be predicted for each grid cell and then aggregated for the stand level, instead of predicting a distribution from the aggregated stand-level characteristics. Trestima required a sufficient sample for reliable results. EMO provided accurate results for the dominating Scots pine but, it could not capture minor admixtures. ABA seemed rather trustworthy in predicting stand characteristics and diameter distribution of standing trees prior to harvesting. Therefore, if up-to-date ABA information is available, only limited benefits can be obtained from stand-specific inventory using Trestima or EMO in mature pine or spruce-dominated forests.

  • Siipilehto, Natural Research Institute Finland (Luke), Management and Production of Renewable Resources, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: jouni.siipilehto@luke.fi (email)
  • Lindeman,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano ORCID ID:E-mail: harri.lindeman@luke.fi
  • Vastaranta, University of Helsinki, Department of Forest Sciences, P.O. Box 62 (Viikinkaari 11), FI-00014 University of Helsinki ORCID ID:E-mail: mikko.vastaranta@helsinki.fi
  • Yu, Finnish Geospatial Research Institute (FGI), Department of Remote Sensing and Photogrammetry, National Land Survey of Finland, P.O. Box 15 (Geodeetinrinne 2), FI-02431, Masala, Finland ORCID ID:E-mail: xiaowei.yu@maanmittauslaitos.fi
  • Uusitalo,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano ORCID ID:E-mail: jori.uusitalo@luke.fi
article id 1106, category Research article
Jena Ferrarese, David Affleck, Carl Seielstad. (2015). Conifer crown profile models from terrestrial laser scanning. Silva Fennica vol. 49 no. 1 article id 1106. https://doi.org/10.14214/sf.1106
Highlights: Crown models are derived from terrestrial laser data for 3 NW USA conifer species; Crown models require only crown length for implementation; Beta and Weibull curves fit to 95th percentile widths describe crown extent; Crown profile curves are species-specific and not interchangeable; Crown shape is not strongly conditioned by tree size or site.
Regional crown profile models were derived for three conifer species of the interior northwestern USA from terrestrial laser scans of eighty-six trees across a range of sizes and growing conditions. Equations were developed to predict crown shape from crown length for Pseudotsuga menziesii, Pinus ponderosa, and Abies lasiocarpa from parametric curves applied to crown-length normalized laser point clouds. The 95th width percentile adequately described each crown’s outer limit; alternate width percentiles produced little profile shape variation. For P. menziesii and P. ponderosa, a scaling parameter-modified beta curve gave the most accurate fit (using cross-validated Mean Absolute Error) to aggregated 95th width percentile points. For A. lasiocarpa, beta and Weibull curves (equivalently modified) produced similar results. For all species, modified beta and Weibull curves fit crown points with less error than conic or cylindrical profiles. Crown profile curves were species-specific; interchanging among species increased error significantly. Laser-derived crown base metrics provided objectivity and consistency, but underestimated field-derived base heights through inclusion of dead branches. Profile curve parameters were not correlated with tree or stand characteristics suggesting that crown shape is not strongly conditioned by size and site factors. However, laser sampling necessarily favored more open growing conditions, potentially under-representing variations in crown shape associated with social position. Overall, Terrrestrial Laser Scanning (TLS) lends itself to detailed measurements of external crown architecture with occlusion-imposed limits to characterization of internal features. Yet, the time and cost of collecting and processing individual tree data precludes use of TLS as a common field sampling tool.
  • Ferrarese, College of Forestry and Conservation, The University of Montana, Missoula, MT, USA; (present) Center for the Environmental Management of Military Lands, 1490 Campus Delivery, Colorado State University, Fort Collins, CO 80523, USA ORCID ID:E-mail: jena.ferrarese@colostate.edu (email)
  • Affleck, College of Forestry and Conservation, University of Montana, Missoula, MT, USA ORCID ID:E-mail: david.affleck@cfc.umt.edu
  • Seielstad, College of Forestry and Conservation, University of Montana, Missoula, MT, USA ORCID ID:E-mail: carl.seielstad@firecenter.umt.edu
article id 1057, category Research article
Jouni Siipilehto, Lauri Mehtätalo. (2013). Parameter recovery vs. parameter prediction for the Weibull distribution validated for Scots pine stands in Finland. Silva Fennica vol. 47 no. 4 article id 1057. https://doi.org/10.14214/sf.1057
Highlights: A parameter recovery method (PRM) was developed for forest stand inventories and compared with previously developed parameter prediction methods (PPM) in Finland; PRM for the 2-parameter Weibull function provided compatibility for the main stand characteristics: stem number, basal area and one of the four optional mean characteristics; PRM provided comparable and at its best, superior accuracy in volume characteristics compared with PPM.
The moment-based parameter recovery method (PRM) has not been applied in Finland since the 1930s, even after a continuation of forest stand structure modelling in the 1980s. This paper presents a general overview of PRM and some useful applications. Applied PRM provided compatibility for the included stand characteristics of stem number (N) and basal area (G) with either mean (D), basal area-weighted mean (DG), median (DM) or basal area-median (DGM) diameter at breast height (dbh). A two-parameter Weibull function was used to describe the dbh-frequency distribution of Scots pine stands in Finland. In the validation, PRM was compared with existing parameter prediction models (PPMs). In addition, existing models for stand characteristics were used for the prediction of unknown characteristics. Validation consisted of examining the performance of the predicted distributions with respect to variation in stand density and accuracy of the localised distributions, as well as accuracy in terms of bias and the RMSE in stand characteristics in the independent test data set. The validation data consisted of 467 randomly selected stands from the National Forest Inventory based plots. PRM demonstrated excellent accuracy if G and N were both known. At its best, PRM provided accuracy that was superior to any existing model in Finland – especially in young stands (mean height < 9 m), where the RMSE in total and pulp wood volumes, 3.6 and 5.7%, respectively, was reduced by one-half of the values obtained using the best performing existing PPM (8.7–11.3%). The unweighted Weibull distribution solved by PRM was found to be competitive with weighted existing PPMs for advanced stands. Therefore, using PRM, the need for a basal area weighted distribution proved unnecessary, contrary to common belief. Models for G and N were shown to be unreliable and need to be improved to obtain more reliable distributions using PRM.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: jouni.siipilehto@metla.fi (email)
  • Mehtätalo, University of Eastern Finland, School of Computing, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.mehtatalo@uef.fi
article id 219, category Research article
Arto Haara, Pekka Leskinen. (2009). The assessment of the uncertainty of updated stand-level inventory data. Silva Fennica vol. 43 no. 1 article id 219. https://doi.org/10.14214/sf.219
Predictions of growth and yield are essential in forest management planning. Growth predictions are usually obtained by applying complex simulation systems, whose accuracy is difficult to assess. Moreover, the computerised updating of old inventory data is increasing in the management of forest planning systems. A common characteristic of prediction models is that the uncertainties involved are usually not considered in the decision-making process. In this paper, two methods for assessing the uncertainty of updated forest inventory data were studied. The considered methods were (i) the models of observed errors and (ii) the k-nearest neighbour method. The derived assessments of uncertainty were compared with the empirical estimates of uncertainty. The practical utilisation of both methods was considered as well. The uncertainty assessments of updated stand-level inventory data using both methods were found to be feasible. The main advantages of the two studied methods include that bias as well as accuracy can be assessed.
  • Haara, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: arto.haara@joensuu.fi (email)
  • Leskinen, Finnish Environment Institute, Research Programme for Production and Consumption, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
article id 237, category Research article
Jussi Peuhkurinen, Matti Maltamo, Jukka Malinen. (2008). Estimating species-specific diameter distributions and saw log recoveries of boreal forests from airborne laser scanning data and aerial photographs: a distribution-based approach. Silva Fennica vol. 42 no. 4 article id 237. https://doi.org/10.14214/sf.237
The low-density airborne laser scanning (ALS) data based estimation methods have been shown to produce accurate estimates of mean forest characteristics and diameter distributions, according to several studies. The used estimation methods have been based on the laser canopy height distribution approach, where various laser pulse height distribution -derived predictors are related to the stand characteristics of interest. This approach requires very delicate selection methods for selecting the suitable predictor variables. In this study, we introduce a new nearest neighbor search method that requires no complicated selection algorithm for choosing the predictor variables and can be utilized in multipurpose situations. The proposed search method is based on Minkowski distances between the distributions extracted from low density ALS data and aerial photographs. Apart from the introduction of a new search method, the aims of this study were: 1) to produce accurate species-specific diameter distributions and 2) to estimate factual saw log recovery, using the estimated height-diameter distributions and a stem data bank. The results indicate that the proposed method is suitable for producing species-specific diameter distributions and volumes at the stand level. However, it is proposed, that the utilization of more extensive and locally emphasized reference data and auxiliary variables could yield more accurate saw log recoveries.
  • Peuhkurinen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Maltamo, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Malinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
article id 271, category Research article
Patrick Insinna, Risto Jalkanen, Bernhard Götz. (2007). Climate impact on 100-year foliage chronologies of Scots pine and Ponderosa pine in the northeast lowlands of Brandenburg, Germany. Silva Fennica vol. 41 no. 4 article id 271. https://doi.org/10.14214/sf.271
Due to differences in the high-frequency signal and mean sensitivity of needle parameters in Scots pine and Ponderosa pine revealed in previous investigations, variance caused by climate factors at a dry site in the northeast lowlands of Brandenburg was investigated. Although water is the general limiting factor for both tree species, there are evident differences in the climate-driven impact on individual needle parameters. Autumn precipitation of the previous year was equally important for Scots pine and Ponderosa pine, but summer precipitation was more significant for the needle parameters of Scots pine. In contrast to precipitation, temperature seems to have a minor impact on needle parameters. Although January temperatures are significant predictors for both species, intercorrelations between needle parameters and summer temperatures were found only for Ponderosa pine. Striking correlation was also found between sun activity and needle production in Ponderosa pine, but not Scots pine, indicating possible adaptation to solar radiation.
  • Insinna, Office for Environmental Protection Liechtenstein, Climate Change Division, P.O. Box 684, FL-9490 Vaduz, Liechtenstein ORCID ID:E-mail: patrick.insinna@aus.llv.li (email)
  • Jalkanen, Rovaniemi Research Unit, Finnish Forest Research Institute, P.O. Box 16, FI-96301 Rovaniemi, Finland ORCID ID:E-mail:
  • Götz, Eberswalde University of Applied Sciences, Department of Forestry, Forest-Botanical Gardens, D-16225 Eberswalde, Germany ORCID ID:E-mail:
article id 332, category Research article
Marc Palahí, Timo Pukkala, Antoni Trasobares. (2006). Calibrating predicted tree diameter distributions in Catalonia, Spain. Silva Fennica vol. 40 no. 3 article id 332. https://doi.org/10.14214/sf.332
Several probability density functions have been used in describing the diameter distributions of forest stands. In a case where both the stand basal area and number of stems per hectare are assessed, the fitted or predicted distribution is scaled using only one of these variables, with the result that the distribution often gives incorrect values for the other variable. Using a distribution that provides incorrect values for known characteristics means wasting information. Calibrating the distribution so that it is compatible with the additional information on stand characteristics is a way to avoid such wasting. This study examined the effect of calibration on the accuracy of the predicted diameter distributions of the main tree species of Catalonia. The distributions were calibrated with and without considering the prediction errors of the frequencies of diameter classes. When prediction errors were assumed, the calibration was done with and without making allowance for estimation errors in the stand level calibration variables. Calibrated distributions were more accurate than non-calibrated in terms of sums of different powers of diameters. The set of calibration variables that gave the most accurate results included six stand variables: number of trees per hectare, stand basal area, basal-area-weighted mean diameter, non-weighted mean diameter, median diameter, and basal area median diameter. Of the tested three-variable combinations the best was: number of trees per hectare, stand basal area, and basal-area-weighted mean diameter. Means were more useful calibration variables than medians.
  • Palahí, Centre Tecnológic Forestal de Catalunya. Passeig Lluis Companys, 23, 08010, Barcelona, Spain ORCID ID:E-mail: marc.palahi@ctfc.es (email)
  • Pukkala, University of Joensuu, Faculty of Forestry, P.O. Box 111, 80101 Joensuu, Finland ORCID ID:E-mail:
  • Trasobares, Foreco Technologies, Av. Diagonal 416, Estudio 2, Barcelona 08037, Spain ORCID ID:E-mail:
article id 368, category Research article
Eero Muinonen. (2005). Generating a raster map presentation of a forest resource by solving a transportation problem. Silva Fennica vol. 39 no. 4 article id 368. https://doi.org/10.14214/sf.368
Necessary tools for raster map generation, for the approach based on the calibration estimator, were developed and implemented. The allocation of the area weight of each pixel to sample plots was formulated as a transportation problem, using a spectral distance measure as a transportation cost, and solved using the transportation simplex algorithm. Pixel level accuracy was calculated for the methods based on the calibration estimator so that the results could be compared with the results of the nearest neighbour estimation, the reference sample plot method (RSP) at pixel level. Local averaging in a 3 x 3 window was performed for each generated raster map as a postprocessing phase to smooth the map. Test plot results were calculated both for the unfiltered raster map and the filtered raster map. RSP produced the smallest RMSE in the pooled test data. Local averaging with a 3 x 3 filter decreased the pixel level error – and the bias – and the differences between the methods are smaller. Without local averaging, the pixel level errors of the methods based on solving the transportation problem were high. Raster map generation using the methods of this study forms an optional part – followed possibly by the classification of the pixel level results – of the whole computation task, when the area weight computation is based on the calibration estimation. For larger areas than in the present study, such as municipalities, the efficiency of the method based on the transportation model must be improved before it is a usable tool, in practice, for raster map generation. For nearest neighbour methods, the area size is not such a problem, because the inventory area is processed pixel by pixel.
  • Muinonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: eero.muinonen@metla.fi (email)
article id 395, category Research article
Lauri Mehtätalo. (2005). Height-diameter models for Scots pine and birch in Finland. Silva Fennica vol. 39 no. 1 article id 395. https://doi.org/10.14214/sf.395
Height-Diameter (H-D) models for two shade-intolerant tree species were estimated from longitudinal data. The longitudinal character of the data was taken into account by estimating the models as random effects models using two nested levels: stand and measurement occasion level. The results show that the parameters of the H-D equation develop over time but the development rate varies between stands. Therefore the development of the parameters is not linked to the stand age but to the median diameter of the basal-area weighted diameter distribution (DGM). Models were estimated with different predictor combinations in order to produce appropriate models for different situations. The estimated models can be localized for a new stand using measured heights and diameters, presumably from different points in time, and the H-D curves can be projected into the future.
  • Mehtätalo, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.mehtatalo@metla.fi (email)
article id 486, category Research article
Arto Haara. (2003). Comparing simulation methods for modelling the errors of stand inventory data. Silva Fennica vol. 37 no. 4 article id 486. https://doi.org/10.14214/sf.486
Forest management planning requires information about the uncertainty inherent in the available data. Inventory data, including simulated errors, are infrequently utilised in forest planning studies for analysing the effects of uncertainty on planning. Usually the errors in the source material are ignored or not taken into account properly. The aim of this study was to compare different methods for generating errors into the stand-level inventory data and to study the effect of erroneous data on the calculation of specieswise and standwise inventory results. The material of the study consisted of 1842 stands located in northern Finland and 41 stands located in eastern Finland. Stand-level ocular inventory and checking inventory were carried out in all study stands by professional surveyors. In simulation experiments the methods considered for error generation were the 1nn-method, the empirical errors method and the Monte Carlo method with log-normal and multivariate log-normal error distributions. The Monte Carlo method with multivariate error distributions was found to be the most flexible simulation method. This method produced the required variation and relations between the errors of the median basal area tree characteristics. However, if the reference data are extensive the 1nn-method, and in certain conditions also the empirical errors method, offer a useful tool for producing error structures which reflect reality.
  • Haara, Finnish Forest Research Institute, Joensuu Research Centre, P.O.Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail: arto.haara@metla.fi (email)
article id 514, category Research article
Jukka Malinen. (2003). Locally adaptable non-parametric methods for estimating stand characteristics for wood procurement planning. Silva Fennica vol. 37 no. 1 article id 514. https://doi.org/10.14214/sf.514
The purpose of this study was to examine the use of the local adaptation of the non-parametric Most Similar Neighbour (MSN) method in estimating stand characteristics for wood procurement planning purposes. Local adaptation was performed in two different ways: 1) by selecting local data from a database with the MSN method and using that data as a database in the basic k-nearest neighbour (k-nn) MSN method, 2) by selecting a combination of neighbours from the neighbourhood where the average of the predictor variables was closest to the target stand predictor variables (Locally Adaptable Neighbourhood (LAN) MSN method). The study data used comprised 209 spruce dominated stands located in central Finland and was collected with harvesters. The accuracy of the methods was analysed by estimating the tree stock characteristics and the log length/diameter distribution produced by a bucking simulation. The local k-nn MSN method was not notably better than the k-nn MSN method, although it produced less biased estimates on the edges of the input space. The LAN MSN method was found to be a more accurate method than the k-nn methods.
  • Malinen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail: jukka.malinen@joensuu.fi (email)
article id 580, category Research article
Susanna Sironen, Annika Kangas, Matti Maltamo, Jyrki Kangas. (2001). Estimating individual tree growth with the k-nearest neighbour and k-Most Similar Neighbour methods. Silva Fennica vol. 35 no. 4 article id 580. https://doi.org/10.14214/sf.580
The purpose of this study was to examine the use of non-parametric methods in estimating tree level growth models. In non-parametric methods the growth of a tree is predicted as a weighted average of the values of neighbouring observations. The selection of the nearest neighbours is based on the differences between tree and stand level characteristics of the target tree and the neighbours. The data for the models were collected from the areas owned by Kuusamo Common Forest in Northeast Finland. The whole data consisted of 4051 tally trees and 1308 Scots pines (Pinus sylvestris L.) and 367 Norway spruces (Picea abies Karst.). Models for 5-year diameter growth and bark thickness at the end of the growing period were constructed with two different non-parametric methods: the k-nearest neighbour regression and k-Most Similar Neighbour method. Diameter at breast height, tree height, mean age of the stand and basal area of the trees larger than the subject tree were found to predict the diameter growth most accurately. The non-parametric methods were compared to traditional regression growth models and were found to be quite competitive and reliable growth estimators.
  • Sironen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail: susanna.sironen@forest.joensuu.fi (email)
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland ORCID ID:E-mail:
  • Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland ORCID ID:E-mail:
article id 579, category Research article
Matti Maltamo, Kalle Eerikäinen. (2001). The Most Similar Neighbour reference in the yield prediction of Pinus kesiya stands in Zambia. Silva Fennica vol. 35 no. 4 article id 579. https://doi.org/10.14214/sf.579
The aim of the study was to develop a yield prediction model using the non-parametric Most Similar Neighbour (MSN) reference method. The model is constructed on stand level but it contains information also on tree level. A 10-year projection period was used for the analysis of stand growth. First, the canonical correlation matrix was calculated for the whole study material using stand volumes at the beginning and at the end of the growth period as independent variables and stand characteristics as dependent variable. Secondly, similar neighbour estimates were searched from the data categories reclassified according to thinnings. Due to this, it was possible to search for growth and yield series which is as accurate as possible both at the beginning and at the end of the growth period. The reliability of the MSN volume predictions was compared to the volumes predicted with the simultaneous yield model. The MSN approach was observed to be more reliable volume predictor than the traditional stand level yield prediction model both in thinned and unthinned stands.
  • Maltamo, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail: matti.maltamo@forest.joensuu.fi (email)
  • Eerikäinen, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
article id 617, category Research article
Jouni Siipilehto. (2000). A comparison of two parameter prediction methods for stand structure in Finland. Silva Fennica vol. 34 no. 4 article id 617. https://doi.org/10.14214/sf.617
The objective of this paper was to predict a model for describing stand structure of tree heights (h) and diameters at breast height (dbh). The research material consisted of data collected from 64 stands of Norway spruce (Picea abies Karst.) and 91 stands of Scots pine (Pinus sylvestris L.) located in southern Finland. Both stand types contained birch (Betula pendula Roth and B. pubescent Ehrh.) admixtures. The traditional univariate approach (Model I) of using the dbh distribution (Johnson’s SB) together with a height curve (Näslund’s function) was compared against the bivariate approaches, Johnson’s SBB distribution (Model II) and Model Ie. In Model Ie within-dbh-class h-variation was included by transforming a normally distributed homogenous error of linearized Näslund’s function to concern real heights. Basal-area-weighted distributions were estimated using the maximum likelihood (ML) method. Species-specific prediction models were derived using linear regression analysis. The models were compared with Kolmogorov-Smirnov tests for marginal distributions, accuracy of stand variables and the dbh-h relationship of individual trees. The differences in the stand characteristics between the models were marginal. Model I gave a slightly better fit for spruce, but Model II was better for pine stands. The univariate Model I resulted in clearly too narrow marginal h-distribution for pine. It is recommended applying of a constrained ML method for reasonable dbh-h relationship instead of using a pure ML method when fitting the SBB model.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland ORCID ID:E-mail: jouni.siipilehto@metla.fi (email)
article id 626, category Research article
Teijo Nikkanen, Seppo Ruotsalainen. (2000). Variation in flowering abundance and its impact on the genetic diversity of the seed crop in a Norway spruce seed orchard. Silva Fennica vol. 34 no. 3 article id 626. https://doi.org/10.14214/sf.626
The variation in flowering abundance was studied in a Norway spruce seed orchard, located in southern Finland (62°13'N, 25°24'E), consisting of 67 clones from northern Finland (64°–67°N). The flowering variation in 1984–1996 was studied at the annual, clonal and graft level. In addition, the genetic diversity of an imaginary seed crop was estimated using a concept of status number. The between-year variation was large in both female and male flowering. Differences in flowering abundance among the clones were large and statistically significant in all the years studied. The average broad-sense heritability values for female and male flowering were 0.37 and 0.38, respectively, but varied considerably from year to year. The correlations between the flowering abundance of the clones in different years were usually positive and significant. However, the correlations for two pairs of successive good flowering years showed that the same clones usually flowered well in the first year in both pairs of years, and the other clones in the second year. The clonal differences in flowering could not be explained by geographic origin, but were more dependent on the graft size. Our results demonstrate that the variation in the ramet number, flowering abundance and pollen contamination must be included when estimating the genetic diversity of the seed crop in a seed orchard. The relative status number of the seed orchard was 84% of the number of clones when the variation in the ramet number was included. The relative status numbers after adjusting for the variation in female and male flowering were on the average 46 and 55%, respectively, and 59% when adjusting for both genders together. Pollen contamination increased the status number considerably.
  • Nikkanen, Finnish Forest Research Institute, Punkaharju Research Station, FIN-58450 Punkaharju, Finland ORCID ID:E-mail: teijo.nikkanen@metla.fi (email)
  • Ruotsalainen, Finnish Forest Research Institute, Punkaharju Research Station, FIN-58450 Punkaharju, Finland ORCID ID:E-mail:
article id 650, category Research article
Jouni Siipilehto. (1999). Improving the accuracy of predicted basal-area diameter distribution in advanced stands by determining stem number. Silva Fennica vol. 33 no. 4 article id 650. https://doi.org/10.14214/sf.650
The objective of this paper was to study to what extent the accuracy of predicted basal-area diameter distributions (DDG) could be improved by means of stem number observations in advanced (H > 10 m) stands. In the Finnish forest management planning (FMP) inventory practice, stem number is determined only in young stands; in older stands stand basal area is used. The study material consisted of sixty stands of Norway spruce (Picea abies Karst.) and ninety-one stands of Scots pine (Pinus sylvestris L.) with birch (Betula pendula Roth and B. pubescens Ehrh.) admixtures in southern and eastern Finland. For test data, 167–292 independent, National Forest Inventory-based, permanent sample plots were used. DDGs were estimated with the maximum likelihood method. Species-specific models for predicting the distribution parameters were derived using regression analysis. The two-parameter Weibull distribution was compared to the three-parameter Johnson’s SB distributions in predicting DDGs. The models were based on either predictors that are consistent with current FMP (model G), or assuming an additional stem number observation (model G+N). The predicted distributions were compared in terms of the derived stand variables: stem number, total and timber volumes. The results were similar in modelling and test data sets. Methods, based on the SB distribution obtained with model (G+N), proved to give the most accurate description of the stand structure. Differences were marginal in stand total volumes. However, the error variation in stem number was 20% to 80% lower than when applying model (G). SB and Weibull distributions gave very much the same results if model (G) was applied.
  • Siipilehto, Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FIN-01301 Vantaa, Finland ORCID ID:E-mail: jouni.siipilehto@metla.fi (email)

Category: Research note

article id 653, category Research note
Desta Fekedulegn, Mairitin P. Mac Siurtain, Jim J. Colbert. (1999). Parameter estimation of nonlinear growth models in forestry. Silva Fennica vol. 33 no. 4 article id 653. https://doi.org/10.14214/sf.653
Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinning Experiment. Formulas that provide good initial values of the parameters are specified. Clear definitions of the parameters of the nonlinear models in the context of the system being modelled are found to be critically important in the process of parameter estimation.
  • Fekedulegn, Department of Statistics, West Virginia University, Eberly College of Arts and Sciences, P.O. Box 6330, Morgantown, WV26506, USA ORCID ID:E-mail: fdesta@stat.wvu.edu (email)
  • Mac Siurtain, University College Dublin, Ireland ORCID ID:E-mail:
  • Colbert, USDA Forest Service, Northeastern Research Station, Morgantown, West Virginia ORCID ID:E-mail:

Category: Article

article id 5609, category Article
Matti Maltamo. (1997). Comparing basal area diameter distributions estimated by tree species and for the entire growing stock in a mixed stand. Silva Fennica vol. 31 no. 1 article id 5609. https://doi.org/10.14214/sf.a8510

The purpose of this study was to compare the Weibull distributions estimated for the entire growing stock of a stand and separately for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst.) in describing the basal area diameter distributions in mixed stands. The material for this study was obtained by measuring 553 stands located in eastern Finland. The parameters of the Weibull distribution were estimated using the method of maximum likelihood. The models for these parameters were derived using regression analysis. Also, some parameter models from previous studies were compared with the measured distribution. The obtained distributions were compared using the diameter sums of the entire growing stock, diameter sums by tree species and of the sawtimber part of the growing stock. The results showed that far more accurate results were obtained when the distributions were formed using parameter models separately for the different tree species than when using parameter models for the entire growing stock. This was already true when considering the entire growing stock of the stand and especially when the results were examined by tree species. When the models for the entire growing stock were applied by tree species in relation to basal areas, the results obtained were overestimates for Norway spruce and underestimates for Scots pine. The models from earlier studies, where parameter models were estimated separately for tree species from the National Forest Inventory data, showed good fits also in regard to the data of this study.

  • Maltamo, ORCID ID:E-mail:
article id 7197, category Article
Erik Lönnroth. (1926). Der stereometrische Bestandesmittelstamm. Acta Forestalia Fennica vol. 30 no. 2 article id 7197. https://doi.org/10.14214/aff.7197
English title: The stereometric mean tree of the stand.

The mean has a great importance in statistics in general and also in forest statistical calculations. The meaning of the average tree and its characteristics is important also for the practical forest mensuration work. However, the question is how are the statistical numbers of a mean tree related to the statistical numbers of the stand.   

Study is based on the strip-wise survey of forests in southern Finland. From that information the 30 sample plots were chosen, 10 of each of most typical forest site types, MT, VT and CT. The stands are of different ages and development classes, varying from 14 to 159 years.

For the determination of the average tree are the statistical numbers of five characteristics needed: volume, basal area, diameter, height and form factor. The stereometric mean tree of the stand can be calculated with only one statistical method and that solution is absolute.

Theoretically and statistically absolute solution for the problem is the continuous solution by the mean that is weighted with the number of stems. This solution however is not very useful in practical sense.

A simple, practical and adequately exact solution for determining the average tree by approximation procedure of a certain arithmetic mean. 

  • Lönnroth, ORCID ID:E-mail:
article id 5563, category Article
Margaret Penner, Hannu Hökkä, Timo Penttilä. (1995). A method for using random parameters in analyzing permanent sample plots. Silva Fennica vol. 29 no. 4 article id 5563. https://doi.org/10.14214/sf.a9214

The use of random parameter models in forestry has been proposed as one method of incorporating different levels of information into prediction equations. By explicitly considering the variance-covariance structure of observations and considering some model parameters as random rather than fixed, one can incorporate more complex error structures in analysing data.

Competition indices and variance component techniques were applied to 92 Scots pine (Pinus sylvestris L.) -dominated permanent sample plots on drained peatlands in Northern Finland. By quantifying stand, plot, and tree level variation, it was possible to identify the level (stand, plot or tree) at which the explanatory variables contributed to the model. The replication of plots within stands revealed little variation among plots within a single stand but significant variation occurred at stand and tree levels. Positive and negative effects of inter-tree competition are identified by examining simple correlation statistics and the random parameter model.

  • Penner, ORCID ID:E-mail:
  • Hökkä, ORCID ID:E-mail:
  • Penttilä, ORCID ID:E-mail:
article id 5553, category Article
Annika Kangas, Kari T. Korhonen. (1995). Generalizing sample tree information with semiparametric and parametric models. Silva Fennica vol. 29 no. 2 article id 5553. https://doi.org/10.14214/sf.a9204

Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model. Examination of spatial distribution of residuals showed that spatial correlation of residuals is lower for semiparametric and mixed models than for parametric models with fixed regressors. Mixed models and semiparametric models can both be used for describing the effect of geographic location on stem form.

  • Kangas, ORCID ID:E-mail:
  • Korhonen, ORCID ID:E-mail:
article id 5553, category Article
Annika Kangas, Kari T. Korhonen. (1995). Generalizing sample tree information with semiparametric and parametric models. Silva Fennica vol. 29 no. 2 article id 5553. https://doi.org/10.14214/sf.a9204

Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model. Examination of spatial distribution of residuals showed that spatial correlation of residuals is lower for semiparametric and mixed models than for parametric models with fixed regressors. Mixed models and semiparametric models can both be used for describing the effect of geographic location on stem form.

  • Kangas, ORCID ID:E-mail:
  • Korhonen, ORCID ID:E-mail:
article id 5270, category Article
Pekka Kilkki, Risto Päivinen. (1986). Weibull function in the estimation of the basal area dbh-distribution. Silva Fennica vol. 20 no. 2 article id 5270. https://doi.org/10.14214/sf.a15449

The paper demonstrates the possibility of using data from small relascope sample plots in the derivation of the regression models which predict the Weibull function parameters for the dbh-distribution. The Weibull parameters describing the basal area dbh-distribution were estimated for relascope sample plots from the Finnish National Forest Inventory. In the first stage of the estimation nonlinear regression analysis was employed to derive initial parameter estimates for the second stage, in which the maximum likelihood method was used. The parameter estimates were employed as dependent variables for the derivation of the regression models; the independent variables comprised of the compartment-wise stand variables generally estimated in ocular inventories.

The PDF includes an abstract in Finnish.

  • Kilkki, ORCID ID:E-mail:
  • Päivinen, ORCID ID:E-mail:
article id 7524, category Article
Jari Varjo. (1997). Change detection and controlling forest information using multi-temporal Landsat TM imagery. Acta Forestalia Fennica no. 258 article id 7524. https://doi.org/10.14214/aff.7524

A method was developed for relative radiometric calibration of single multitemporal Landsat TM image, several multitemporal images covering each other, and several multitemporal images covering different geographical locations. The radiometrically calibrated different images were used for detecting rapid changes on forest stands. The nonparametric Kernel method was applied for change detection. The accuracy of the change detection was estimated by inspecting the image analysis results in field.

The change classification was applied for controlling the quality of the continuously updated forest stand information. The aim was to ensure that all the manmade changes and any forest damages were correctly updated including the attribute and stand delineation information. The image analysis results were compared with the registered treatments and the stand information base. The stands with discrepancies between these two information sources were recommended to be field inspected.

  • Varjo, ORCID ID:E-mail:
article id 7630, category Article
Esko Mikkonen. (1983). Eräiden matemaattisen ohjelmoinnin menetelmien käyttö puun korjuun ja kuljetuksen sekä tehdaskäsittelyn menetelmävalinnan apuvälineenä. Acta Forestalia Fennica no. 183 article id 7630. https://doi.org/10.14214/aff.7630
English title: The usefulness of some techniques of the mathematical programming as a tool for the choice of timber harvesting system.

The applicability of five mathematical programming methods, namely standard linear programming, parametric programming, goal programming, mixed integer programming and integer programming is discussed as a planning tool for the choice of wood procurement method.

Theoretically, the goal programming approach seems to be the best routine for mathematical handling of problems related to wood procurement. The parametric approach must include enough large post-optimality analysis routine. If the effect of the variables expressed with different measures is to be studied, interpretation of the economic information given by the approach becomes a problem. The other drawback is that the approach does not allow determination of the hierarchy of the goals objectively as they depend on the subjective preferences of the decision maker.

From the practical point of view, standard linear programming is the best method if the objective function can be formulated in economic terms, for instance. If there are several goals to be attained or satisfied the best method is goal programming.

According to the sub-studies, every method under consideration can be used as a solution routine for the minimization of wood procurement costs. In cost minimization the best methods are goal programming and standard linear programming. The best method for harvesting system evaluation purposes is parametric because it allows varied cost calculations within a certain cost range. The best method for harvesting equipment investment planning is mixed integer programming with binary decision variables.

The more complicated and restricted the problem environment is, the better the mathematical programming approach will be, also in harvesting related problems.

The PDF includes a summary in English.

  • Mikkonen, ORCID ID:E-mail:
article id 7630, category Article
Esko Mikkonen. (1983). Eräiden matemaattisen ohjelmoinnin menetelmien käyttö puun korjuun ja kuljetuksen sekä tehdaskäsittelyn menetelmävalinnan apuvälineenä. Acta Forestalia Fennica no. 183 article id 7630. https://doi.org/10.14214/aff.7630
English title: The usefulness of some techniques of the mathematical programming as a tool for the choice of timber harvesting system.

The applicability of five mathematical programming methods, namely standard linear programming, parametric programming, goal programming, mixed integer programming and integer programming is discussed as a planning tool for the choice of wood procurement method.

Theoretically, the goal programming approach seems to be the best routine for mathematical handling of problems related to wood procurement. The parametric approach must include enough large post-optimality analysis routine. If the effect of the variables expressed with different measures is to be studied, interpretation of the economic information given by the approach becomes a problem. The other drawback is that the approach does not allow determination of the hierarchy of the goals objectively as they depend on the subjective preferences of the decision maker.

From the practical point of view, standard linear programming is the best method if the objective function can be formulated in economic terms, for instance. If there are several goals to be attained or satisfied the best method is goal programming.

According to the sub-studies, every method under consideration can be used as a solution routine for the minimization of wood procurement costs. In cost minimization the best methods are goal programming and standard linear programming. The best method for harvesting system evaluation purposes is parametric because it allows varied cost calculations within a certain cost range. The best method for harvesting equipment investment planning is mixed integer programming with binary decision variables.

The more complicated and restricted the problem environment is, the better the mathematical programming approach will be, also in harvesting related problems.

The PDF includes a summary in English.

  • Mikkonen, ORCID ID:E-mail:

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