Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees

SUMMARY: This study aimed at evaluating the performance of different models based on Artificial neural networks (ANN) to estimate the total height of eucalyptus trees (Eucalyptus spp.), reducing the number of measurements in the field. Forty-eight ANN were tested, different from each other by the nu...

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Autores principales:	Dantas,Daniel, Rodrigues Pinto,Luiz Otávio, de Castro Nunes Santos Terra,Marcela, Calegario,Natalino, Romarco de Oliveira,Marcio Leles
Lenguaje:	English
Publicado:	Universidad Austral de Chile, Facultad de Ciencias Forestales 2020
Materias:	artificial neural network machine learning stem volume Schumacher and Hall
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92002020000300353
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spelling	oai:scielo:S0717-920020200003003532020-12-21Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus treesDantas,DanielRodrigues Pinto,Luiz Otáviode Castro Nunes Santos Terra,MarcelaCalegario,NatalinoRomarco de Oliveira,Marcio Leles artificial neural network machine learning stem volume Schumacher and Hall SUMMARY: This study aimed at evaluating the performance of different models based on Artificial neural networks (ANN) to estimate the total height of eucalyptus trees (Eucalyptus spp.), reducing the number of measurements in the field. Forty-eight ANN were tested, different from each other by the number of trees used as training sample, number of trees used to calculate the dominant height and use of variables (a) categorical, (b) categorical and continuous and (c) continuous, except for the diameter at 1.30 meters above the ground (DBH), used in all combinations. Estimates of height obtained by ANN were compared with values observed and estimates obtained by a hypsometric model. The ANN that showed the best results were used for the height estimation in forest inventory data for further application in the Schumacher and Hall volumetric model. The proposed models were efficient to estimate the total height of eucalyptus trees and allowed the expressive reduction of the number of trees to be measured in forest inventory. The best model found is composed of five trees as training sample, one as test sample and one as validation sample; dominant height coming from the height of the tallest tree in the plot; categorical variable Clone and continuous variables DBH, DBH dominant and basal area of the plot.info:eu-repo/semantics/openAccessUniversidad Austral de Chile, Facultad de Ciencias ForestalesBosque (Valdivia) v.41 n.3 20202020-12-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92002020000300353en10.4067/S0717-92002020000300353
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	artificial neural network machine learning stem volume Schumacher and Hall
spellingShingle	artificial neural network machine learning stem volume Schumacher and Hall Dantas,Daniel Rodrigues Pinto,Luiz Otávio de Castro Nunes Santos Terra,Marcela Calegario,Natalino Romarco de Oliveira,Marcio Leles Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
description	SUMMARY: This study aimed at evaluating the performance of different models based on Artificial neural networks (ANN) to estimate the total height of eucalyptus trees (Eucalyptus spp.), reducing the number of measurements in the field. Forty-eight ANN were tested, different from each other by the number of trees used as training sample, number of trees used to calculate the dominant height and use of variables (a) categorical, (b) categorical and continuous and (c) continuous, except for the diameter at 1.30 meters above the ground (DBH), used in all combinations. Estimates of height obtained by ANN were compared with values observed and estimates obtained by a hypsometric model. The ANN that showed the best results were used for the height estimation in forest inventory data for further application in the Schumacher and Hall volumetric model. The proposed models were efficient to estimate the total height of eucalyptus trees and allowed the expressive reduction of the number of trees to be measured in forest inventory. The best model found is composed of five trees as training sample, one as test sample and one as validation sample; dominant height coming from the height of the tallest tree in the plot; categorical variable Clone and continuous variables DBH, DBH dominant and basal area of the plot.
author	Dantas,Daniel Rodrigues Pinto,Luiz Otávio de Castro Nunes Santos Terra,Marcela Calegario,Natalino Romarco de Oliveira,Marcio Leles
author_facet	Dantas,Daniel Rodrigues Pinto,Luiz Otávio de Castro Nunes Santos Terra,Marcela Calegario,Natalino Romarco de Oliveira,Marcio Leles
author_sort	Dantas,Daniel
title	Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
title_short	Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
title_full	Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
title_fullStr	Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
title_full_unstemmed	Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
title_sort	reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees
publisher	Universidad Austral de Chile, Facultad de Ciencias Forestales
publishDate	2020
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92002020000300353
work_keys_str_mv	AT dantasdaniel reductionofsamplingintensityinforestinventoriestoestimatethetotalheightofeucalyptustrees AT rodriguespintoluizotavio reductionofsamplingintensityinforestinventoriestoestimatethetotalheightofeucalyptustrees AT decastronunessantosterramarcela reductionofsamplingintensityinforestinventoriestoestimatethetotalheightofeucalyptustrees AT calegarionatalino reductionofsamplingintensityinforestinventoriestoestimatethetotalheightofeucalyptustrees AT romarcodeoliveiramarcioleles reductionofsamplingintensityinforestinventoriestoestimatethetotalheightofeucalyptustrees
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Reduction of sampling intensity in forest inventories to estimate the total height of eucalyptus trees

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