Artificial Neural Networks for Estimating Tree Volume in the Brazilian Savanna

Abstract

This paper seeks to estimate tree volumes of different species from the Brazilian savanna by using artificial neural networks and by making comparisons of results with estimates obtained from traditional volumetric equations. Data was obtained from 15 squared samples of 400 m² in an area of 29.6 ha. In each plot, breast height diameter (D) (diameter at 1.30 m from soil), total height (Ht) and commercial height (Hc) of all individuals with D equals or higher than 3.0 cm were measured. Afterwards, each tree was felled for volume measurement. Huber method was used considering measurement of stem diameters with more than 3.0 cm. Obtained data was used to train artificial neural networks (ANN) and to adjust volumetric equations to estimate total and commercial volume of trees. This study has shown that ANN and regression models are efficient for obtaining estimated volumes of trees in the Brazilian savanna. This suggests that artificial neural networks, that take into consideration species as a categorical input variable and were data trained, presented better results than those that are trained without categorical input. REDES NEURAIS ARTIFICIAIS PARA ESTIMAR O VOLUME DE ÁRVORES NO CERRADORESUMO: Neste artigo buscou-se estimar os volumes de árvores de diferentes espécies do Cerrado usando redes neurais artificiais e fazer comparações dos resultados com estimativas obtidas a partir de equações volumétricas tradicionais. Os dados foram coletados em 15 parcelas de 400 m² em uma área de 29,6 ha. Em cada parcela, o diâmetro da altura do peito (D) (diâmetro a 1,30 m do solo), a altura total (Ht) e a altura comercial (Hc) de todos os indivíduos com D igual ou superior a 3,0 cm foram medidos. Depois, cada árvore foi derrubada para obtenção do volume. O método de Huber foi usado considerando a medida dos diâmetros do fuste até 3,0 cm. Os dados obtidos foram utilizados para treinar redes neurais artificiais (RNA) e ajustar equações volumétricas para estimar o volume total e comercial das árvores. Este estudo mostrou que as RNA e as equações volumétricas são eficientes para a obtenção de volumes estimados de árvores no Cerrado. As redes neurais artificiais, que consideram a espécie como uma variável categórica de entrada, apresentaram melhores resultados do que aquelas que são treinadas sem essa variável.

ANÁLISE QUANTITATIVA BIOMÉTRICA E HÍDRICA DOS FRUTOS E SEMENTES DA ESPÉCIE Delonix regia (Boger ex Hook) Raf.

“…The ANNs presented satisfactory results, indicating that they were adequate and accurate for the proposed estimate and, among the networks, the ANN 4 was the one that presented the best results. Although similarity of RNA 4 was observed, with the results obtained with the tapering function of Kozak (2004) BINOTI et al, 2014;RIBEIRO et al, 2016, LACERDA et al, 2017, de altura (BINOTI et al, 2013;VENDRUSCOLO et al, 2015, do diâmetro relativo e estudo da forma MENDONÇA et al, 2015;SCHIKOWSKI et al, 2015;VENDRUSCOLO et al, 2016;MARTINS et al, 2016;CAMPOS et al, 2017;MARTINS et al, 2017), do diâmetro e altura (VIEIRA et al, 2018), em crescimento e produção (CASTRO et al, 2013;BINOTI et al, 2015).…”

Fauna Ameaçada Nas Rodovias

“…KEYWORDS: Forest Management; tapering; diameters along the shaft. (BINOTI et al, 2014;RIBEIRO et al, 2016, LACERDA et al, 2017, de altura (BINOTI et al, 2013;VENDRUSCOLO et al, 2015, do diâmetro relativo e estudo da forma MENDONÇA et al, 2015;SCHIKOWSKI et al, 2015;VENDRUSCOLO et al, 2016;MARTINS et al, 2016;SILVA et al, 2016;CAMPOS et al, 2017;MARTINS et al, 2017), do diâmetro e altura (VIEIRA et al, 2018), em crescimento e produção (CASTRO et al, 2013;BINOTI et al, 2015).…”

Artificial Neural Networks Applied in Forest Biometrics and Modeling: State of the Art (January/2007 to July/2018)

“…In other words, the output refers to the site classification based on the site index observed in the different classes with amplitude variation." Lacerda et al (2017) This study's essence was to portray that the use of ANN can be seen as a highly feasible tool to estimate the volume of trees, considering different species of the Brazilian savanna. As a complement, it created comparisons between the estimates of the networks with some volumetric equations.…”