Recursive diameter prediction and volume calculation of eucalyptus trees using Multilayer Perceptron Networks

  • Soares F
  • Flôres E
  • Cabacinha C
 et al. 
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A major challenge in forest management is the ability to quickly and accurately predict bole volume of standing trees. This study presents a new model that uses Multilayer Perceptron (MLP) artificial neural networks for predicting tree diameters values. The model requires three diameter measures at the base of the tree, and recursively predicts other diameter measures. The predicted diameters allow for calculating tree volume using the Smalian method. The performance of the proposed model was satisfactory when compared with data obtained from tree scaling and volume equations. © 2011 Elsevier B.V.

Author-supplied keywords

  • Estimating diameter
  • Forest inventory
  • Multilayer Perceptron
  • Recursive prediction
  • Volumetric equations

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  • Fabrízzio Alphonsus A M N Soares

  • Edna Lúcia Flôres

  • Christian Dias Cabacinha

  • Gilberto Arantes Carrijo

  • Antônio Cláudio Paschoarelli Veiga

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