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- W654801716 abstract "Sweden is covered by 60 % forestland, and most of it is used in forestry. There is a debate about the forestry methods in Sweden, where clear felling is the most commonly used practice, and alternate methods are being developed. Some of these methods, for example the Lubeck model, is focused on producing the best suited forest for a site, based on the environmental conditions. That forest would probably be of the natural forest type of that location.With this study a model is developed to predict natural forest types based on easily available GIS-data and without using remote sensing. Remote sensing is not considered to be useful in this particular case, since only the already existing vegetation can be analyzed using that method. Existing forests are likely to have been planted, and does not necessarily correspond to the type of vegetation that would develop, were there no human impact.The study was conducted by using forested areas that could be assumed to be natural (within nature reserves and other protected areas) in Askersund municipality, Orebro county, Sweden. An additive Generalized Linear Model (GZLM) has been used, and the prediction is based on soil, bedrock, elevation data and ground water data.The results from the first test, based on the training points on which the model was built, and the validation based on new, independent points from different forest areas, differ. The first test indicate that prediction works well for several of the forest types, while the validation gives the opposite results and shows that the prediction does not actually work.If the model was further developed and would become a working tool, it could make forest management easier and more effective, for example when continuous forestry is carried out. Field work could be concentrated to areas where the forest has been predicted to be of desired type." @default.
- W654801716 created "2016-06-24" @default.
- W654801716 creator A5024822786 @default.
- W654801716 date "2014-01-01" @default.
- W654801716 modified "2023-09-27" @default.
- W654801716 title "En modell som förutsäger naturlig skogstyp utifrån geografik information" @default.
- W654801716 hasPublicationYear "2014" @default.
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