Predicting fir trees stem diameters using Artificial Neural Network models

Abstract

The financial exploitation of forests constitutes an important part of human activity. This effort is being made in order to conserve the sustainable exploitation while avoiding the degradation of the environment. One of the most important operations in forest mensuration is the estimation of the volume of sample trees. Such estimation may be used in order to conduct a large stand inventory, construct volume tables, develop tree competition and growth models, predict tree mortality from diameter growth, and implement a number of other activities. Efficiency, the trade-off between cost and precision, is of paramount importance in the estimation of volume.