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    Author(s): Lutz Fehrmann; Christoph Kleinn
    Date: 2007
    Source: In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the seventh annual forest inventory and analysis symposium; October 3-6, 2005; Portland, ME. Gen. Tech. Rep. WO-77. Washington, DC: U.S. Department of Agriculture, Forest Service: 251-259.
    Publication Series: Other
    Station: Washington Office
    PDF: View PDF  (1.36 MB)

    Description

    Allometric biomass models are typically site and species specific. They are mostly based on a low number of independent variables such as diameter at breast height and tree height. Because of relatively small datasets, their validity is limited to the set of conditions of the study, such as site conditions and diameter range. One challenge in the context of the current climate change discussion is to develop more general approaches for reliable biomass estimation. One alternative approach to widely used regression modelling are nonparametric techniques.

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    Citation

    Fehrmann, Lutz; Kleinn, Christoph. 2007. A k-nearest neighbor approach for estimation of single-tree biomass. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the seventh annual forest inventory and analysis symposium; October 3-6, 2005; Portland, ME. Gen. Tech. Rep. WO-77. Washington, DC: U.S. Department of Agriculture, Forest Service: 251-259.

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