%0 Research article
%T Imputing mean annual change to estimate current forest attributes
%A Eskelson, Bianca N. I.
%A Barrett, Tara M.
%A Temesgen, Hailemariam
%D 2009
%J Silva Fennica
%V 43
%N 4
%R doi:10.14214/sf.185
%U https://silvafennica.fi/article/185
%X When a temporal trend in forest conditions is present, standard  estimates from paneled forest inventories can be biased. Thus methods  that use more recent remote sensing data to improve estimates are  desired. Paneled inventory data from national forests in Oregon and  Washington, U.S.A., were used to explore three nearest neighbor  imputation methods to estimate mean annual change of four forest  attributes (basal area/ha, stems/ha, volume/ha, biomass/ha). The  randomForest imputation method outperformed the other imputation  approaches in terms of root mean square error. The imputed mean annual  change was used to project all panels to a common point in time by  multiplying the mean annual change with the length of the growth period  between measurements and adding the change estimate to the previously  observed measurements of the four forest attributes. The resulting  estimates of the mean of the forest attributes at the current point in  time outperformed the estimates obtained from the national standard  estimator.