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Articles by Jukka Malinen

Category : Research article

article id 10371, category Research article

Katalin Waga, Jukka Malinen, Timo Tokola. (2021). Locally invariant analysis of forest road quality using two different pulse density airborne laser scanning datasets. Silva Fennica vol. 55 no. 1 article id 10371. https://doi.org/10.14214/sf.10371

Keywords: ALS; DEM; forest road quality; reference DEM; unpaved forest road

Highlights: Airborne laser scanning is used to assess forest road quality; High-pulse data analysis classified roads with good performance; Two-step classification further improved the accuracy; A reference surface improved the classification results of the low pulse data; 66–75% of the roads were correctly classified using the reference surface.

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Two different pulse density airborne laser scanning datasets were used to develop a quality assessment methodology to determine how airborne laser scanning derived variables with the use of reference surface can determine forest road quality. The concept of a reference DEM (Digital Elevation Model) was used to guarantee locally invariant topographic analysis of road roughness. Structural condition, surface wear and flatness were assessed at two test sites in Eastern Finland, calculating surface indices with and without the reference DEM. The high pulse density dataset (12 pulses m^–2) gave better classification results (77% accuracy of the correctly classified road sections) than the low pulse density dataset (1 pulse m^–2). The use of a reference DEM increased the precision of the road quality classification with the low pulse density dataset when the classification was performed in two-steps. Four interpolation techniques (Inverse Weighted Distance, Kriging, Natural Neighbour and Spline) were compared, and spline interpolation provided the best classification. The work shows that applying a spline reference DEM it is possible to identify 66% of the poor quality road sections and 78% of the good ones. Locating these roads is essential for road maintenance.

Waga, Faculty of Science and Forestry, University of Eastern Finland, Yliopistokatu 7, FI-80100 Joensuu, Finland https://orcid.org/0000-0003-1496-7012 E-mail: katalin.waga@uef.fi
Malinen, Faculty of Science and Forestry, University of Eastern Finland, Yliopistokatu 7, FI-80100 Joensuu, Finland; Metsäteho Ltd., Vernissakatu 1, FI-01300 Vantaa, Finland https://orcid.org/0000-0002-5023-1056 E-mail: jukka.malinen@uef.fi
Tokola, Faculty of Science and Forestry, University of Eastern Finland, Yliopistokatu 7, FI-80100 Joensuu, Finland E-mail: timo.tokola@uef.fi

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

Keywords: stem quality; bucking; non-parametric prediction; database; assortment recovery; value recovery

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.

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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 E-mail: jukka.malinen@uef.fi
Kilpeläinen, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: harri.kilpelainen@luke.fi
Verkasalo, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: erkki.verkasalo@luke.fi

article id 1293, category Research article

Jukka Malinen, Mika Haring, Harri Kilpeläinen, Erkki Verkasalo. (2015). Comparison of alternative roundwood pricing systems – a simulation approach. Silva Fennica vol. 49 no. 3 article id 1293. https://doi.org/10.14214/sf.1293

Keywords: simulation; pricing; roundwood

Highlights: A discrete event simulation model was developed for studying roundwood pricing systems; For a single buyer, pricing based on residual value appraisal produced (RVA) 4.87 per cent higher wood paying capability and 3.70 per cent higher stumpage price than pricing based on average unit prices; As the number of buyers using RVA increases, the competition increased and the advantage decreased.

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In a closed market, roundwood buyers pricing system affect the roundwood flow from the stands to different roundwood users. If a buyer is capable to discriminate higher value stands from low quality stands better than its competitors, the buyer should be able to buy better raw material. In the study, a discrete event simulation was used to examine the effect of residual value appraisal (RVA) -based pricing of roundwood by log dimensions and grades compared to the traditional pricing based on average unit prices (UP) of roundwood assortments on roundwood flow. The core of the simulation model was the data containing 51 pine dominated stands from southern Finland. Sample trees were theoretically bucked by the bucking simulator in order to estimate the volumes, dimensions and grades of the logs and roundwood assortments. The simulation model of roundwood markets included four roundwood buyers, two corporations and two saw milling enterprises. The main finding of the study was that the buyers who use RVA gains an advantage and receives better quality compared to buyers who use UP. As the number of buyers using RVA increases, the competition increased and the advantage decreased.

Malinen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: jukka.malinen@uef.fi
Haring, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mika.haring@gmail.com
Kilpeläinen, Natural Resources Institute Finland (Luke), Bio-based business and industry, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: harri.kilpelainen@luke.fi
Verkasalo, Natural Resources Institute Finland (Luke), Bio-based business and industry, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: erkki.verkasalo@luke.fi

article id 203, category Research article

Matti Maltamo, Jussi Peuhkurinen, Jukka Malinen, Jari Vauhkonen, Petteri Packalén, Timo Tokola. (2009). Predicting tree attributes and quality characteristics of Scots pine using airborne laser scanning data. Silva Fennica vol. 43 no. 3 article id 203. https://doi.org/10.14214/sf.203

Keywords: LIDAR; alpha shape; crown height; height metrics; k-MSN; timber quality

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The development of airborne laser scanning (ALS) during last ten years has provided new possibilities for accurate description of the living tree stock. The forest inventory applications of ALS data include both tree and area-based plot level approaches. The main goal of such applications has usually been to estimate accurate information on timber quantities. Prediction of timber quality has not been focused to the same extent. Thus, in this study we consider here the prediction of both basic tree attributes (tree diameter, height and volume) and characteristics describing tree quality more closely (crown height, height of the lowest dead branch and sawlog proportion of tree volume) by means of high resolution ALS data. The tree species considered is Scots pine (Pinus sylvestris), and the field data originate from 14 sample plots located in the Koli National Park in North Karelia, eastern Finland. The material comprises 133 trees, and size and quality variables of these trees were modeled using a large number of potential independent variables calculated from the ALS data. These variables included both individual tree recognition and area-based characteristics. Models for the dependent tree characteristics to be considered were then constructed using either the non-parametric k-MSN method or a parametric set of models constructed simultaneously by the Seemingly Unrelated Regression (SUR) approach. The results indicate that the k-MSN method can provide more accurate tree-level estimates than SUR models. The k-MSN estimates were in fact highly accurate in general, the RMSE being less than 10% except in the case of tree volume and height of the lowest dead branch.

Maltamo, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: matti.maltamo@joensuu.fi
Peuhkurinen, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: jp@nn.fi
Malinen, Finnish Forest Research Institute, Joensuu Research Unit, FI-80101 Joensuu, Finland E-mail: jm@nn.fi
Vauhkonen, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: jv@nn.fi
Packalén, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: pp@nn.fi
Tokola, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: tt@nn.fi

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

Keywords: diameter distribution; non-parametric estimation; pre-harvest measurement; stem data bank

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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 E-mail: jp@nn.fi
Maltamo, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mm@nn.fi
Malinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jm@nn.fi

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

Keywords: stand characteristics; local non-parametric estimation; MSN method; wood procurement planning

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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 E-mail: jukka.malinen@joensuu.fi

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