Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2024
Sammendrag
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Sammendrag
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Forfattere
Anne Rørholt Margrete Steinnes Erik Engelien Gunnhild Søgaard Rune Eriksen Arvid SvenssonSammendrag
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Forfattere
Binbin Xiang Maciej Wielgosz Theodora Kontogianni Torben Peters Stefano Puliti Rasmus Astrup Konrad SchindlerSammendrag
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Sammendrag
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Forfattere
Klemens Schadauer Rasmus Astrup Johannes Breidenbach Jonas Fridman Stephan Gräber Michael Köhl Kari T. Korhonen Vivian Kvist Johannsen Francois Morneau Risto Päivinen Thomas RiedelSammendrag
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2023
Sammendrag
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Sammendrag
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Sammendrag
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Forfattere
Ana María De Lera Garrido Terje Gobakken Marius Hauglin Erik Næsset Ole Martin BollandsåsSammendrag
The aim of this study was to analyze the accuracy of predictions of dominant height, mean height, basal area, and volume from the nationwide forest attribute map (SR16). The analysis took advantage of field observations from 33 different forest inventory projects across Norway used for validation. Forest attributes for more than 5000 plots were predicted using non-stratified and stratified models of SR16 and the predictions were compared against corresponding ground reference values. Finally, the effect of different factors that might have influenced the prediction errors were analyzed using partial least squared regression (PLSR) to determine under which conditions the SR16 is less apt. The overall results across all plots were adequate (RMSE of 10%, MD of 2% for dominant and mean height; RMSE of 28%, MD of 4% for basal area; RMSE of 31%, MD of 5% for volume). However, when the accuracy was assessed locally for each inventory project, large differences in accuracy were observed. The MD% values for some inventory projects were substantial (>30% for basal area and volume). The results showed that stratification did not necessarily improve the results and that factors related to the forest structure had the greatest impact on the PLSR analysis.