Calibrating predicted diameter distribution with additional information

Abstract

The diameter distribution of the growing stock is an essential starting point in many forest management planning problems. There are several methods for predicting the diameter distribution of a stand, varying from methods which utilize theoretical distribution functions to nonparametric methods. Usually the predicted diameter distribution is scaled so that the stem number corresponds to the measured value. However, if stem number and basal area are both known, it may be difficult to predict a distribution that gives correct estimates for both these characteristics. Such diameter distributions can be obtained using an approach adopted from sampling theory - calibration estimation. In this study, the diameter distributions of Scots pine were predicted with two different methods, the Weibull and percentile based methods, and then calibrated with additional information. The calibration reduced the RMSE of stand variables computed from the predicted distribution.