%0 Research article
%T Locally adaptable non-parametric methods for estimating stand characteristics for wood procurement planning
%A Malinen, Jukka
%D 2003
%J Silva Fennica
%V 37
%N 1
%R doi:10.14214/sf.514
%U https://silvafennica.fi/article/514
%X The purpose of this study was to examine the use of the local adaptation  of the non-parametric Most Similar Neighbour (MSN) method in estimating  stand characteristics for wood procurement planning purposes. Local  adaptation was performed in two different ways: 1) by selecting local  data from a database with the MSN method and using that data as a  database in the basic k-nearest neighbour (k-nn) MSN method, 2) by  selecting a combination of neighbours from the neighbourhood where the  average of the predictor variables was closest to the target stand  predictor variables (Locally Adaptable Neighbourhood (LAN) MSN method).  The study data used comprised 209 spruce dominated stands located in  central Finland and was collected with harvesters. The accuracy of the  methods was analysed by estimating the tree stock characteristics and  the log length/diameter distribution produced by a bucking simulation.  The local k-nn MSN method was not notably better than the k-nn MSN  method, although it produced less biased estimates on the edges of the  input space. The LAN MSN method was found to be a more accurate method  than the k-nn methods.