Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2019
Authors
Frank A. Maas Mekjell MelandAbstract
No abstract has been registered
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M Natic D Dabic Zagorac Jasminka Milivojevic Mekjell Meland Milica Fotiric-AksicAbstract
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Mekjell MelandAbstract
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Mekjell MelandAbstract
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Misganu Debella-GiloAbstract
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Siri Vatsø Haugum Casper Tai Christiansen Alexander Vågenes Pål Thorvaldsen Liv Guri Velle Vigdis VandvikAbstract
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Authors
Jens Kattge Gerhard Bönisch Sandra Díaz Sandra Lavorel Iain Colin Prentice Paul Leadley Susanne Tautenhahn Gijsbert D.A. Werner Tuomas Aakala Mehdi Abedi Alicia T.R. Acosta George C. Adamidis Kairi Adamson Masahiro Aiba Cécile H. Albert Julio M. Alcántara Carolina Alcázar C. Izabela Aleixo Hamada Ali Bernard Amiaud Christian Ammer Mariano M. Amoroso Madhur Anand Carolyn Anderson Niels Anten Joseph Antos Deborah Mattos Guimarães Apgaua Tia-Lynn Ashman Degi Harja Asmara Gregory P. Asner Michael Aspinwall Owen Atkin Isabelle Aubin Lars Baastrup-Spohr Khadijeh Bahalkeh Michael Bahn Timothy Baker William J. Baker Jan P. Bakker Dennis Baldocchi Jennifer Baltzer Arindam Banerjee Anne Baranger Jos Barlow Diego R. Barneche Zdravko Baruch Denis Bastianelli John Battles William Bauerle Marijn Bauters Bente Jessen Graae Joseph Hawes Knut Anders Hovstad Kristin Odden Nystuen Graciela Rusch Mia Vedel SørensenAbstract
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Authors
Rasmus Astrup Johannes Rahlf Knut Bjørkelo Misganu Debella-Gilo Arnt Kristian Gjertsen Johannes BreidenbachAbstract
This paper describes the development and utility of the Norwegian forest resources map (SR16). SR16 is developed using photogrammetric point cloud data with ground plots from the Norwegian National Forest Inventory (NFI). First, an existing forest mask was updated with object-based image analysis methods. Evaluation against the NFI forest definitions showed Cohen's kappa of 0.80 and accuracy of 0.91 in the lowlands and a kappa of 0.73 and an accuracy of 0.96 in the mountains. Within the updated forest mask, a 16×16 m raster map was developed with Lorey's height, volume, biomass, and tree species as attributes (SR16-raster). All attributes were predicted with generalized linear models that explained about 70% of the observed variation and had relative RMSEs of about 50%. SR16-raster was segmented into stand-like polygons that are relatively homogenous in respect to tree species, volume, site index, and Lorey's height (SR16-vector). When SR16 was utilized in a combination with the NFI plots and a model-assisted estimator, the precision was on average 2–3 times higher than estimates based on field data only. In conclusion, SR16 is useful for improved estimates from the Norwegian NFI at various scales. The mapped products may be useful as additional information in Forest Management Inventories.