Eucalyptus Volume Estimation for Eucalyptus Clones Trees Using Artificial Neural Networks

The forest inventory is an instrument of great importance for the healthy management of forest resources. Although It can be used in many applications, for example, to quantify trees or to identify the species of a settlement, the volume is one of the most critical elements for exploration of a specific area. However, it is very challenging to find methods that can accurately calculate the volume of trees without raising costs. Therefore, this study presents an approach with artificial neural networks for the prediction of diameters and calculation of the volume of eucalyptus clones. We proposed models that depend on or not the total height of the tree, which is a measure expensive to obtain in the field. A result shows our proposed methods are up-and-coming to the traditional techniques, besides reduce the total features used for the volume estimation and can support forest inventory automation.