%0 Research article
%T Comparing simulation methods for modelling the errors of stand inventory data
%A Haara, Arto
%D 2003
%J Silva Fennica
%V 37
%N 4
%R doi:10.14214/sf.486
%U https://silvafennica.fi/article/486
%X Forest management planning requires information about the uncertainty  inherent in the available data. Inventory data, including simulated  errors, are infrequently utilised in forest planning studies for  analysing the effects of uncertainty on planning. Usually the errors in  the source material are ignored or not taken into account properly. The  aim of this study was to compare different methods for generating errors  into the stand-level inventory data and to study the effect of  erroneous data on the calculation of specieswise and standwise inventory  results. The material of the study consisted of 1842 stands located in  northern Finland and 41 stands located in eastern Finland. Stand-level  ocular inventory and checking inventory were carried out in all study  stands by professional surveyors. In simulation experiments the methods  considered for error generation were the 1nn-method, the empirical  errors method and the Monte Carlo method with log-normal and  multivariate log-normal error distributions. The Monte Carlo method with  multivariate error distributions was found to be the most flexible  simulation method. This method produced the required variation and  relations between the errors of the median basal area tree  characteristics. However, if the reference data are extensive the  1nn-method, and in certain conditions also the empirical errors method,  offer a useful tool for producing error structures which reflect  reality.