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Articles by Kari T. Korhonen

Category: Research article

article id 1410, category Research article
Seppo Nevalainen, Juho Matala, Kari T. Korhonen, Antti Ihalainen, Ari Nikula. (2016). Moose damage in National Forest Inventories (1986–2008) in Finland. Silva Fennica vol. 50 no. 2 article id 1410. https://doi.org/10.14214/sf.1410
Highlights: Almost 100 000 stands were studied; The proportion of damage doubled during the study period; Tree species mixture had a clear effect on the damage frequency; The damage was more common in mineral soils than in peatlands, in artificially than in naturally regenerated stands and in stands that needed thinning or clearing or in which soil preparation was used.

The occurrence of moose damage was studied using data from three National Forest Inventories (NFIs) accomplished between 1986 and 2008 in Finland. The combined data included a total of 97 390 young stands. The proportion of moose damage increased from 3.6% to 8.6% between the 8th NFI (1986–1994) and the 10th NFI (2004–2008). The majority (75%) of the damage occurred in Scots pine-dominated stands. The proportion of damage was higher in aspen-dominated stands than in stands dominated by any other tree species. The tree species mixture also had a clear effect on the occurrence of damage. Pure Scots pine stands had less damage than mixed Scots pine stands, and moose damage decreased linearly with the increasing proportion of Scots pine. Stands on mineral soil had more frequent moose damage than stands on peatlands. The fertility class of the site had no straightforward effect on the damage frequency. Artificially regenerated stands had more damage than naturally regenerated stands. Accomplished soil preparation measures and the need for thinning or clearing operations increased moose damage. High proportions of moose damage in young stands were found around the country. In the 10th NFI, the largest concentration of damage was found in southwestern Finland. Our study shows the temporal and spatial changes in the occurrence of moose damage and pinpoints some important silvicultural factors affecting the relative risk of young stands over a large geographical area.

  • Nevalainen, Natural Resources Institute Finland (Luke), Management and Production of Renewable Resources, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: seppo.nevalainen@luke.fi (email)
  • Matala, Natural Resources Institute Finland (Luke), Management and Production of Renewable Resources, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: juho.matala@luke.fi
  • Korhonen, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: kari.t.korhonen@luke.fi
  • Ihalainen, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: antti.ihalainen@luke.fi
  • Nikula, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 16, FI-96301 Rovaniemi, Finland ORCID ID:E-mail: ari.nikula@luke.fi
article id 983, category Research article
Sakari Tuominen, Juho Pitkänen, Andras Balazs, Kari T. Korhonen, Pekka Hyvönen, Eero Muinonen. (2014). NFI plots as complementary reference data in forest inventory based on airborne laser scanning and aerial photography in Finland. Silva Fennica vol. 48 no. 2 article id 983. https://doi.org/10.14214/sf.983
Highlights: Using NFI plots in forest management inventories could provide a way for rationalising forest inventory data acquisition; NFI plots were used as additional reference data in laser scanning and aerial image based forest inventory; NFI plots improved the estimates of some forest variables; There are differences between the two inventory types that cause difficulties in combining the data.
In Finland, there are currently two, parallel sample-plot-based forest inventory systems, which differ in their methodologies, sampling designs, and objectives. One is the National Forest Inventory (NFI), aimed at unbiased inventory results at national and regional level. The other is the Forest Centre’s management-oriented forest inventory based on interpretation of airborne laser scanning and aerial images, with the aim of locally accurate stand-level forest estimates. The National Forest Inventory utilises relascope sample plots with systematic cluster sampling. This inventory method is optimised for accuracy of regional volume estimates. In contrast, the management-oriented forest inventory utilises circular sample plots with an allocation system covering certain pre-defined forest classes in the inventory area. This method is optimised to produce reference data for interpretation of the remote-sensing materials in use. In this study, we tested the feasibility of the National Forest Inventory sample plots in provision of additional reference data for the management-oriented inventory. Various combinations of NFI plots and management inventory plots were tested in the interpretation of the laser and aerial-image data. Adding NFI plots in the reference data generally improved the accuracy of the volume estimates by tree species but not the estimates of total volume or stand mean height and diameter. The difference between the plot types in the NFI and management inventories causes difficulties in combination of the two datasets.
  • Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: sakari.tuominen@metla.fi (email)
  • Pitkänen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: juho.pitkanen@metla.fi
  • Balazs, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: andras.balazs@metla.fi
  • Korhonen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: kari.t.korhonen@metla.fi
  • Hyvönen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: pekka.hyvonen@metla.fi
  • Muinonen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: eero.muinonen@metla.fi
article id 275, category Research article
Lauri Korhonen, Kari T. Korhonen, Pauline Stenberg, Matti Maltamo, Miina Rautiainen. (2007). Local models for forest canopy cover with beta regression. Silva Fennica vol. 41 no. 4 article id 275. https://doi.org/10.14214/sf.275
Accurate field measurement of the forest canopy cover is too laborious to be used in extensive forest inventories. A possible alternative to the separate canopy cover measurements is to utilize the correlations between the percent canopy cover and easier-to-measure forest variables, especially the basal area. A fairly new analysis technique, the beta regression, is specially designed for modelling percentages. As an extension to the generalized linear models, the beta regression takes into account the distribution of the model residuals, and uses a logistic link function to ensure logical predictions. In this study, the beta regression method was found to perform well in conifer dominated study area located in central Finland. The same model shape, with basal area, tree height and an additional predictor (Scots pine: site fertility, Norway spruce: percentage of hardwoods) as independent variables, produced good results for both pine and spruce dominated sites. The models had reasonably high pseudo R-squared values (pine: 0.91, spruce: 0.87) and low standard errors (pine: 6.3%, spruce: 5.9%) for the fitting data, and also performed well in a cross validation test. The models were also tested on separate test plots located in a different geographical area, where the prediction errors were slightly larger (pine: 8.8%, spruce: 7.4%). In pine plots, the model fit was further improved by introducing additional predictors such as stand age and density. This improved also the performance of the models in the cross validation test, but weakened the results for the external data set. Our results indicated that the beta regression method offers a noteworthy alternative to separate canopy cover measurements, especially if time is limited and the models can be applied in the same region where the modelling data were collected.
  • Korhonen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.korhonen@joensuu.fi (email)
  • Korhonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Stenberg, Univ. of Helsinki, Dept of Forest Resource Management, P.O. BOX 27, FI-00014 University of Helsinki, 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:
  • Rautiainen, Univ. of Helsinki, Dept of Forest Resource Management, P.O. BOX 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 315, category Research article
Lauri Korhonen, Kari T. Korhonen, Miina Rautiainen, Pauline Stenberg. (2006). Estimation of forest canopy cover: a comparison of field measurement techniques. Silva Fennica vol. 40 no. 4 article id 315. https://doi.org/10.14214/sf.315
Estimation of forest canopy cover has recently been included in many forest inventory programmes. In this study, after discussing how canopy cover is defined, different ground-based canopy cover estimation techniques are compared to determine which would be the most feasible for a large scale forest inventory. Canopy cover was estimated in 19 Scots pine or Norway spruce dominated plots using the Cajanus tube, line intersect sampling, modified spherical densiometer, digital photographs, and ocular estimation. The comparisons were based on the differences in values acquired with selected techniques and control values acquired with the Cajanus tube. The statistical significance of the differences between the techniques was tested with the nonparametric Kruskall-Wallis analysis of variance and multiple comparisons. The results indicate that different techniques yield considerably different canopy cover estimates. In general, labour intensive techniques (the Cajanus tube, line intersect sampling) provide unbiased and more precise estimates, whereas the estimates provided by fast techniques (digital photographs, ocular estimation) have larger variances and may also be seriously biased.
  • Korhonen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland ORCID ID:E-mail: lauri.korhonen@joensuu.fi (email)
  • Korhonen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland ORCID ID:E-mail:
  • Rautiainen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland ORCID ID:E-mail:
  • Stenberg, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland ORCID ID:E-mail:
article id 587, category Research article
Erkki Tomppo, Kari T. Korhonen, Juha Heikkinen, Hannu Yli-Kojola. (2001). Multi-source inventory of the forests of the Hebei Forestry Bureau, Heilongjiang, China. Silva Fennica vol. 35 no. 3 article id 587. https://doi.org/10.14214/sf.587
A multi-source forest inventory method is applied to the estimation of forest resources in the area of the Hebei Forest Bureau in Heilongjiang province in North-East China. A stratified systematic cluster sampling design was utilised in field measurements. The design was constructed on the basis of information from earlier stand-level inventories, aerial orthophotographs, experiences from other sampling inventories and the available budget. Sample tree volumes were estimated by means of existing models. New models were constructed and their parameters estimated for tallied tree volumes and volume increments. The estimates for the area of the Bureau were computed from field measurements, and for the areas of the forest farms estimated from field measurements and satellite images. A k-nearest neighbour method was utilised. This method employing satellite image data makes it possible to estimate all variables, particularly for smaller areas than that possible using field measurements only. The methods presented, or their modifications, could also be applied to the planning and realisation of forest inventories elsewhere in Temperate or Boreal zones. The inventory in question gave an estimate of 114 m3/ha (the multi-source inventory 119 m3/ha) instead of 72 m3/ha as previously estimated from available information. Totally nineteen tree species, genera of species or tree species groups were identified (Appendix 1). The forests were relatively young, 60% of them younger than 40 years and 85% younger than 60 years.
  • Tomppo, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail: erkki.tomppo@metla.fi (email)
  • Korhonen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail:
  • Heikkinen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail:
  • Yli-Kojola, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail:
article id 636, category Research article
Tuula Nuutinen, Hannu Hirvelä, Jari Hynynen, Kari Härkönen, Hannu Hökkä, Kari T. Korhonen, Olli Salminen. (2000). The role of peatlands in Finnish wood production – an analysis based on large-scale forest scenario modelling. Silva Fennica vol. 34 no. 2 article id 636. https://doi.org/10.14214/sf.636
Using the Finnish MELA model, a set of scenarios were produced and used to map the possibilities and risks surrounding the utilisation of peatlands in wood production in Finland. One of the scenarios was an estimate of allowable-cut calculated by maximising the net present value of the future revenues using a four per cent interest rate subject to non-decreasing flow of wood, saw logs and net income over a 50-year period, and net present value after the 50 year period greater or equal than in the beginning. The estimate for maximum regionally sustained removal in 1996–2005 was 68 million m3 per year – approaching 74 million m3 during the next decades. In this scenario, 14 per cent of all cuttings during the period 1996–2005 would be made on peatlands, which comprise ca. 31 per cent of the total area of forestry land. By the year 2025, the proportion of peatland cuttings would increase to over 20 per cent. The increase in future cutting possibilities on peatlands compensated for a temporary decrease in cuttings and growing stock on mineral soils. The allowable-cut effect was especially pronounced in northern Finland, where peatlands play an important role in wood production. In addition, the sensitivity of cutting possibilities for assumptions related to growth and price were analysed. The estimate of maximum sustainable yield as defined here seems to be fairly robust on the whole, except in northern Finland where the cutting scenarios were sensitive to the changes in the price of birch pulpwood. The proportion of peatland stands that are profitable for timber production depends on the interest rate: the higher the rate of interest the less peatland stands are thinned. The effect of cutting profile on future logging conditions and resulting costs were analysed in two forestry centres. If clear cuttings on mineral soils are to be cut first, an increase in future logging costs is inevitable.
  • Nuutinen, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail: tuula.nuutinen@metla.fi (email)
  • Hirvelä, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Hynynen, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Härkönen, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Hökkä, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Korhonen, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:
  • Salminen, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail:

Category: Article

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 5520, category Article
Kari T. Korhonen. (1993). Mixed estimation in calibration of volume functions of Scots pine. Silva Fennica vol. 27 no. 4 article id 5520. https://doi.org/10.14214/sf.a15681

Regression models for estimating stem volume of Scots pine (Pinus sylvestris L.) were constructed using sample tree data measured in the 7th and 8th National Forest Inventory of Finland. Stem volume were regressed on diameter, basal area of growing stock, and geographic location. The results of the study show that using second order trend surface to describe the geographic variation of the residuals gives satisfactory results. Using mixed estimation for combining old and new sample tree data improves the efficiency of an inventory. The weight of the prior information must be low, because remarkable differences in stem form was found in the two inventories.

The PDF includes an abstract in Finnish.

  • Korhonen, ORCID ID:E-mail:
article id 5491, category Article
Kari T. Korhonen. (1992). Calibration of upper diameter models in large scale forest inventory. Silva Fennica vol. 26 no. 4 article id 5491. https://doi.org/10.14214/sf.a15652

Models for estimating the upper diameter of trees were constructed using sample tree data measured in the 7th National Forest Inventory in Finland. Calibration of the models was tested with data from the 8th National Forest Inventory. The results showed that using mixed estimation for combining the two data sets improves the reliability of the models. Models and methods used in this study can be recommended for use in forest inventories.

The PDF includes an abstract in Finnish.

  • Korhonen, ORCID ID:E-mail:
article id 5444, category Article
Kari T. Korhonen, Matti Maltamo. (1991). The evaluation of forest inventory designs using correlation functions. Silva Fennica vol. 25 no. 2 article id 5444. https://doi.org/10.14214/sf.a15598

Correlation functions of the mean volume, land use class and soil class were estimated using the data of the Finnish National Forest Inventory. Estimated functions were used for approximating the standard error of e.g. the mean volume of a cluster of plots. Standard error estimates can be used for comparing different inventory designs.

The PDF includes an abstract in Finnish.

  • Korhonen, ORCID ID:E-mail:
  • Maltamo, ORCID ID:E-mail:

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