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Articles by Inka Bohlin

Category: Research article

article id 10573, category Research article
Jari Miina, Inka Bohlin, Torgny Lind, Jonas Dahlgren, Kari Härkönen, Tuula Packalen, Anne Tolvanen. (2021). Lessons learned from assessing the cover and yield of bilberry and lingonberry using the national forest inventories in Finland and Sweden. Silva Fennica vol. 55 no. 5 article id 10573. https://doi.org/10.14214/sf.10573
Keywords: forest management planning; berry models; field measurements; predictions
Highlights: Model-based predictions of the berry yields of an average crop year are produced using the Finnish National Forest Inventory (NFI); Inventory-based estimates of seasonal berry yields are produced using the Swedish NFI observations; The inventory-based method provides seasonal estimates, whereas models can be utilised to integrate vegetation cover and berry yields in numerical multi-objective forest planning.
Abstract | Full text in HTML | Full text in PDF | Author Info

Bilberry (Vaccinium myrtillus L.) and lingonberry (V. vitis-idaea L.) can be a part of healthy diet and are important for many animals. Two approaches are described to assessing their vegetation cover and berry yield via national forest inventory (NFI) observations. The aim was to provide estimates and predictions of the abundance and yield of the species at regional and national levels in Finland and Sweden. In Finland, the model-based predictions are used in evaluating the impacts of cutting intensity on forest berries needed in forest-related decision making. In Sweden, seasonal inventory-based estimates are used to evaluate the annual national and regional berry yields, and in a forecasting system aimed at large public and berry enterprises. Based on the NFI sample plots measured between 2014 and 2018, the total annual yields are estimated to be 208 Mkg of bilberry and 246 Mkg of lingonberry on productive forest land (increment at least 1 m3 ha–1 year–1) in Finland, and 336 and 382 Mkg respectively in Sweden (average of NFI inventories in 2015–2019). The predicted development of berry yields is related to the intensity of cuttings in alternative forest management scenarios: lower removals favoured bilberry, and higher removals lingonberry. The model-based method describes the effects of stand development and management on berry yields, whereas the inventory-based method can calibrate seasonal estimates through field observations. In providing spatially and timely more accurate information concerning seasonal berry yields, an assessment of berry yields should involve the elements of both inventory-based and model-based approaches described in this study.

  • Miina, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland ORCID https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi (email)
  • Bohlin, Swedish University of Agricultural sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, S-901 83 Umeå, Sweden E-mail: inka.bohlin@slu.se
  • Lind, Swedish University of Agricultural sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, S-901 83 Umeå, Sweden E-mail: torgny.lind@slu.se
  • Dahlgren, Swedish University of Agricultural sciences (SLU), Department of Forest Resource Management, Skogsmarksgränd, S-901 83 Umeå, Sweden E-mail: jonas.dahlgren@slu.se
  • Härkönen, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: kari.harkonen@luke.fi
  • Packalen, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland; Ministry of Agriculture and Forestry of Finland, P.O. Box 30, FI-00023 Government, Finland E-mail: tuula.packalen@mmm.fi
  • Tolvanen, Natural Resources Institute Finland (Luke), Paavo Havaksentie 3, FI-90014 University of Oulu, Finland E-mail: anne.tolvanen@luke.fi
article id 2021, category Research article
Jonas Bohlin, Inka Bohlin, Jonas Jonzén, Mats Nilsson. (2017). Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory. Silva Fennica vol. 51 no. 2 article id 2021. https://doi.org/10.14214/sf.2021
Keywords: airborne laser scanning; National Forest Inventory; photogrammetry; aerial images; forest attribute estimation; image matching; large area
Highlights: Image based forest attribute map generated using NFI plots show similar accuracy as currently used LiDAR based forest attribute map; Also similar accuracies were found for different forest types; Aerial images from leaf-off season is not recommended.
Abstract | Full text in HTML | Full text in PDF | Author Info

Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping.

  • Bohlin, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden ORCID http://orcid.org/0000-0002-3318-5967 E-mail: jonas.bohlin@slu.se (email)
  • Bohlin, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden ORCID http://orcid.org/0000-0003-1224-6684 E-mail: inka.bohlin@slu.se
  • Jonzén, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden E-mail: jonas.jonzen@slu.se
  • Nilsson, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden ORCID http://orcid.org/0000-0001-7394-6305 E-mail: mats.nilsson@slu.se

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