Janne Uuttera, Harri Hyppänen. (1997). Relationship between forest management planning units and spatial distribution of forest habitat components in Koli National Park. Silva Fennica vol. 31 no. 4 article id 5637. https://doi.org/10.14214/sf.a8539

Keywords: Finland; forest management planning; forest habitat distribution; Geographic Information Systems; kriging-interpolation; Koli National park

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This study examined the relationships between forest management planning units and patches formed by forest habitat components. The test area used was a part of Koli National Park in North Karelia, eastern Finland. Forest management planning units (i.e. forest compartments) were defined by using a traditional method of Finnish forestry which applies aerial photographs and compartment-wise field inventory. Patches of forest habitat components were divided according to subjective rules by using a chosen set of variables depicting the edaphic features and vegetation of a forest habitat. The spatial distribution of the habitat components was estimated with the kriging-interpolation based on systematically located sample plots. The comparisons of the two patch mosaics were made by using the standard tools of GIS. The results of the study show that forest compartment division does not correlate very strongly with the forest habitat pattern. On average, the mean patch size of the forest habitat components is greater and the number of these patches lower compared to forest compartment division. However, if the forest habitat component distribution had been considered, the number of the forest compartments would have at least doubled after intersection.

Uuttera, E-mail: ju@mm.unknown
Hyppänen, E-mail: hh@mm.unknown

Category : Research article

article id 22026, category Research article

Annika Kangas, Mari Myllymäki, Lauri Mehtätalo. (2023). Understanding uncertainty in forest resources maps. Silva Fennica vol. 57 no. 2 article id 22026. https://doi.org/10.14214/sf.22026

Keywords: autocorrelation; ensemble modelling; kriging; quantile; random forest; sequential Gaussian simulation

Highlights: Forest resources maps without uncertainty assessment may lead to false impression of precision; Suitable tools for visualization of map products are lacking; Kriging method provided accurate uncertainty assessment for pixel-level predictions; Quantile random forest algorithm slightly underestimated the pixel-level uncertainties; With simulation it is possible to assess the uncertainty also for landscape-level characteristics.

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

Maps of forest resources and other ecosystem services are needed for decision making at different levels. However, such maps are typically presented without addressing the uncertainties. Thus, the users of the maps have vague or no understanding of the uncertainties and can easily make wrong conclusions. Attempts to visualize the uncertainties are also rare, even though the visualization would be highly likely to improve understanding. One complication is that it has been difficult to address the predictions and their uncertainties simultaneously. In this article, the methods for addressing the map uncertainty and visualize them are first reviewed. Then, the methods are tested using laser scanning data with simulated response variable values to illustrate their possibilities. Analytical kriging approach captured the uncertainty of predictions at pixel level in our test case, where the estimated models had similar log-linear shape than the true model. Ensemble modelling with random forest led to slight underestimation of the uncertainties. Simulation is needed when uncertainty estimates are required for landscape level features more complicated than small areas.

Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, 80101 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
Myllymäki, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0002-2713-7088 E-mail: mari.myllymaki@luke.fi
Mehtätalo, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, 80101 Joensuu, Finland https://orcid.org/0000-0002-8128-0598 E-mail: lauri.mehtatalo@luke.fi

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