Annika S. Kangas, Jyrki Kangas. (1999). Optimization bias in forest management planning solutions due to errors in forest variables. Silva Fennica vol. 33 no. 4 article id 651. https://doi.org/10.14214/sf.651

Keywords: forest planning; uncertainty; prediction; decision analysis

Abstract | View details | Full text in PDF | Author Info

The yield of various forest variables is predicted by means of a simulation system to provide information for forest management planning. These predictions contain many kinds of uncertainty, for example, prediction and measurement errors. Inevitably, this has an effect on forest management planning. It is well known that uncertainty in the forest yields causes optimistic bias in the observed values of the objective function. This bias increases with the error variances. The amount of bias, however, also depends on the error structure and the relations between the objective variables. In this paper, the effect of uncertainty in forest yields on optimization is studied by simulation. The effect of two different sources of error, the correlation structure of these errors and relations among the objective variables are considered, as well as the effect of two different optimization approaches. The relations between the objective variables and the error structure had a notable effect on the optimization results.

Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: annika.kangas@metla.fi
Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland E-mail: jk@nn.fi

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