%0 Research article
%T Bayesian estimation of diameter distribution during harvesting
%A Uusitalo, Jori
%A Puustelli, Anne
%A Kivinen, Veli-Pekka
%A Nummi, Tapio
%A Sinha, Bikas K.
%D 2006
%J Silva Fennica
%V 40
%N 4
%R doi:10.14214/sf.321
%U https://silvafennica.fi/article/321
%X This research aims to combine two different data sets with Bayesian  statistics in order to predict the diameter distribution of trees at  harvest. The parameters of prior distribution are derived from the  forest management plans supplemented by additional ocular information.  We derive the parameters for the sample data from the first trees  harvested, and then create the posterior distribution within the  Bayesian framework. We apply the standard normal distribution to  construct diameter (dbh) distributions, although many other theoretical  distributions have been proved better with dbh data available. The  methodology developed is then tested on nine mature spruce (Picea abies)  dominated stands, on which the normal distribution seems to work well  in mature spruce stands. The tests indicate that prediction of diameter  distribution for the whole stand based on the first trees harvested is  not wise, since it tends to give inaccurate predictions. Combining the  first trees harvested with prior information seems to increase the  reliability of predictions.