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Traditionally, satellite-based approaches to vegetation classification over large areas rely upon one main input dataset, and the use of trained algorithms for classification. Results from this study indicate that an automated approach, which combines a priori information specific to a region, greatly enhances the value of the final result. Results from this study could be applied to other large boreal regions with modifications, and the techniques developed here could be further tested.</abstract>
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