Percentile based basal area diameter distribution models for Scots pine, Norway spruce and birch species.

By Annika S. Kangas, Matti Maltamo. 2000

48 citations recorded by the source corpus.

Information about diameter distribution is used for predicting stand total volume, timber volume and stand growth for forest management planning. Often, the diameter distribution is obtained by predicting the parameters of some probability density function, using means and sums of tree characters as predictors. However, the results have not always been satisfactory: the predicted distributions practically always have a similar shape. Also, multimodal distributions cannot be obtained. However, diameter distribution can also be predicted using distribution-free methods. In the percentile method, the diameters at certain percentiles of the distribution are predicted with models. The empirical diameter distribution function is then obtained by interpolating between the predicted diameters. In this paper, models for diameters at 12 percentiles of stand basal area are presented for Scots pine, Norway spruce and birch species. Two sets of models are estimated: a set with and one without number of stems as a predictor. Including the number of stems as a predictor improved the volume and saw timber volume estimates for all species, but the improvements were especially high for number of stems estimates obtained from the predicted distribution. The use of number of stems as predictor in models is based on the possibility of including this characteristic to measured stand variables.

Subfields: Environmental Engineering, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/882642504894a48cbefc9bc618f3188599c5e82f

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In Environmental Engineering

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Estimating percentile-based diameter distributions in uneven-sized Norway spruce stands using airborne laser scanner data (2007, methodology): “Different distribution functions have been proposed to model empirical diameter distributions, where the Weibull is the most frequently used (e.g. Bailey & Dell, 1973; Kangas & Maltamo, 2000b).”
Parameter recovery vs. parameter prediction for the Weibull distribution validated for Scots pine stands in Finland (2013, methodology): “This has been performed mostly to improve the accuracy in stem volume and assortments (see Kangas and Maltamo 2000a; Kangas and Maltamo 2002; Mabvirura et al. 2002).”
Performance of percentile based diameter distribution prediction and Weibull method in independent data sets (2000, methodology): “Kangas and Maltamo (2000a) used this approach to calibrate the predicted frequencies of a diameter distribution.”
Weibull and percentile models for lidar-based estimation of basal area distribution (2005, methodology): “The work by Kangas and Maltamo (2000) is an example of such a study in boreal forest based on extensive field data.”