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Annika S. Kangas (email), Jyrki Kangas

Optimization bias in forest management planning solutions due to errors in forest variables

Kangas A.S., Kangas J. (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

Abstract

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.

Keywords
decision analysis; forest planning; prediction; uncertainty

Author Info
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland ORCID ID:E-mail annika.kangas@metla.fi (email)
  • Kangas, Finnish Forest Research Institute, Kannus Research Station, P.O. Box 44, FIN-69101 Kannus, Finland ORCID ID:

Received 27 July 1999 Accepted 16 November 1999 Published 31 December 1999

Available at https://doi.org/10.14214/sf.651 | Download PDF

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