Performance of percentile based diameter distribution prediction and Weibull method in independent data sets

Diameter distribution is used in most forest management planning packages for predicting stand volume, timber volume and stand growth. The prediction of diameter distribution can be based on parametric distribution functions, distribution-free parametric prediction methods or purely n...

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Main Authors: Kangas, Annika, Maltamo, Matti
Format: Article
Language:English
Published: Finnish Society of Forest Science 2000-01-01
Series:Silva Fennica
Online Access:https://www.silvafennica.fi/article/620
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spelling doaj-82ddb467b47947988b99466d9a05ae0d2020-11-25T03:05:52ZengFinnish Society of Forest ScienceSilva Fennica2242-40752000-01-0134410.14214/sf.620Performance of percentile based diameter distribution prediction and Weibull method in independent data setsKangas, AnnikaMaltamo, Matti Diameter distribution is used in most forest management planning packages for predicting stand volume, timber volume and stand growth. The prediction of diameter distribution can be based on parametric distribution functions, distribution-free parametric prediction methods or purely non-parametric methods. In the first case, the distribution is obtained by predicting the parameters of some probability density function. In a distribution-free percentile method, the diameters at certain percentiles of the distribution are predicted with models. In non-parametric methods, the predicted distribution is a linear combination of similar measured stands. In this study, the percentile based diameter distribution is compared to the results obtained with the Weibull method in four independent data sets. In the case of Scots pine, the other methods are also compared to k-nearest neighbour method. The comparison was made with respect to the accuracy of predicted stand volume, saw timber volume and number of stems. The predicted percentile and Weibull distributions were calibrated using number of stems measured from the stand. The information of minimum and maximum diameters were also used, for re-scaling the percentile based distribution or for parameter recovery of Weibull parameters. The accuracy of the predicted stand characteristics were also compared for calibrated distributions. The most reliable results were obtained using the percentile method with the model set including number of stems as a predictor. Calibration improved the results in most cases. However, using the minimum and maximum diameters for parameter recovery proved to be inefficient.https://www.silvafennica.fi/article/620
collection DOAJ
language English
format Article
sources DOAJ
author Kangas, Annika
Maltamo, Matti
spellingShingle Kangas, Annika
Maltamo, Matti
Performance of percentile based diameter distribution prediction and Weibull method in independent data sets
Silva Fennica
author_facet Kangas, Annika
Maltamo, Matti
author_sort Kangas, Annika
title Performance of percentile based diameter distribution prediction and Weibull method in independent data sets
title_short Performance of percentile based diameter distribution prediction and Weibull method in independent data sets
title_full Performance of percentile based diameter distribution prediction and Weibull method in independent data sets
title_fullStr Performance of percentile based diameter distribution prediction and Weibull method in independent data sets
title_full_unstemmed Performance of percentile based diameter distribution prediction and Weibull method in independent data sets
title_sort performance of percentile based diameter distribution prediction and weibull method in independent data sets
publisher Finnish Society of Forest Science
series Silva Fennica
issn 2242-4075
publishDate 2000-01-01
description Diameter distribution is used in most forest management planning packages for predicting stand volume, timber volume and stand growth. The prediction of diameter distribution can be based on parametric distribution functions, distribution-free parametric prediction methods or purely non-parametric methods. In the first case, the distribution is obtained by predicting the parameters of some probability density function. In a distribution-free percentile method, the diameters at certain percentiles of the distribution are predicted with models. In non-parametric methods, the predicted distribution is a linear combination of similar measured stands. In this study, the percentile based diameter distribution is compared to the results obtained with the Weibull method in four independent data sets. In the case of Scots pine, the other methods are also compared to k-nearest neighbour method. The comparison was made with respect to the accuracy of predicted stand volume, saw timber volume and number of stems. The predicted percentile and Weibull distributions were calibrated using number of stems measured from the stand. The information of minimum and maximum diameters were also used, for re-scaling the percentile based distribution or for parameter recovery of Weibull parameters. The accuracy of the predicted stand characteristics were also compared for calibrated distributions. The most reliable results were obtained using the percentile method with the model set including number of stems as a predictor. Calibration improved the results in most cases. However, using the minimum and maximum diameters for parameter recovery proved to be inefficient.
url https://www.silvafennica.fi/article/620
work_keys_str_mv AT kangasannika performanceofpercentilebaseddiameterdistributionpredictionandweibullmethodinindependentdatasets
AT maltamomatti performanceofpercentilebaseddiameterdistributionpredictionandweibullmethodinindependentdatasets
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