We demonstrate how multidimensional scaling can be used to combine forest inventory field data and airborne laser scanner data to obtain both predictions and model-assisted estimation of a tree stem diameter distribution.
The size distribution of forest trees is important both for management planning and analysis purposes. Yet field samples are rarely large enough to assuage a desired accuracy of a direct estimation in all areas of interest. Improvements in spatial coverage and accuracy are possible with a census—or a very large sample of one or more cost-effective auxiliary variables that can inform one about the tree size distribution. The objective of this study is to demonstrate how a relative frequency distribution of canopy heights from airborne laser scanner data can be used to improve direct estimates of a tree size distribution. Multidimensional scaling is used to link a relative frequency distribution of canopy heights to an observed plot-level distribution of tree size. A multivariate linear model can be used for both predictions and model-assisted estimation of a tree stem diameter distribution. Multidimensional scaling can provide a multivariate linear link between two relative frequency distributions and is therefore ideally suited for both stand-level predictions and design-based inference of tree size distributions.
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Magnussen S, Renaud J-P 2016. Multidimensional scaling of first-return airborne laser echoes for prediction and model-assisted estimation of a distribution of tree stem diameters. Ann. For. Sci.: 1-10. 10.1007/s13595-016-0581-2.