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.
2010
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Tore SkrøppaAbstract
The Svalbard Global Seed Vault provides facilities for the safety deposit of samples of seed of distinct genetic resources of importance to humanity, under black box arrangements and in permafrost conditions supplemented by refrigeration in accordance with internationally agreed standards. The Seed Vault was established by the Norwegian Government in 2008 at 78 degrees North in the Norwegian village of Longyearbyen, on Svalbard, the farthest north you can travel in the world on regularly scheduled commercial jet flight. It is managed in a tripartite arrangement between the Norwegian Ministry of Agriculture and Food, the Global Crop Diversity Trust and the Nordic Genetic Resource Center. The last organisation is responsible for the day to day operation and management and organises deposits in the Seed Vault. The Seed Vault offers the most secure back-up possible for a worldwide network of genebanks that together conserve and make available the biological foundation of agriculture. It contains duplicates of collections of all the world’s major seed crops and a huge range of minor crops. The Seed Vault has a capacity of 4.5 million distinct samples. The seeds are stored in “black-box conditions”, meaning that seed storage boxes remain the property of the institution that sent them, and are not even opened by any party other than the depositor. The storage is provided free of charge. At present, there are more than half a million seed samples in the Vault, origination from 212 countries of the world.
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Ievina SturiteAbstract
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Mette Vaarst Elisabeth Gratzer Michael Walkenhorst Silvia Ivemeyer Jan Brinkman Solveig March Lindsay k Whistance Gidi Smolders Elisabeth Stöger Johann Huber Christine Leeb Stephen Roderick Christoph Winckler Britt IF Henriksen Pip Nicholas Berit Hansen Cecilie Marie MejdellAbstract
In: I. Darnhofer and M. Grötzer: Building sustainable rural futures, Proceedings of the 9th European IFSA Symposium, 4-7 July 2010, Vienna (Austria), WS 1.8, pp. 683-691. Universität für Bodenkultur, Vienna (ISBN 978-3-200-01908-9).
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Jari Vauhkonen Liviu Ene Svein Solberg Marius Hauglin Vegard Lien Petteri Packalén Terje Gobakken Erik Næsset Timo Tokola Matti MaltamoAbstract
The aim of this study was to validate and compare single-tree detection algorithms under different forest conditions. Field data and corresponding airborne laser scanning (ALS) data were acquired from boreal forests in Norway and Sweden, coniferous and broadleaved forests in Germany, and pulpwood plantations in Brazil. The data represented a variety of forest types from pure Eucalyptus stands with known ages and planting densities to conifer-dominated Scandinavian forests and more complex deciduous canopies in Central Europe. ALS data were acquired using different sensors with pulse densities varying between the data sets. Field data in varying extent were associated with each ALS data set for training purposes. Treetop positions were extracted using altogether six different algorithms developed in Finland, Germany, Norway and Sweden, and the accuracy of tree detection and height estimation was assessed. Furthermore, the weaknesses and strengths of the methods under different forest conditions were analyzed. The results showed that forest structure and density strongly affected the performance of all algorithms. The differences in performance between methods were more pronounced for tree detection than for height estimation. The algorithms showed a slightly better performance in the conditions for which they were developed, while some could be adapted by different parameterization according to training with local data. The results of this study may help guiding the choice of method under different conditions and may be of great value for future refinement of the single-tree detection algorithms.
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No abstract has been registered