Computational techniques applied to volume and biomass estimation of trees in brazilian savanna

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dc.creatorJeferson Pereiramartins Silva
dc.creatorMaria Naruna Felix de Almeida
dc.creatorMárcia Rodrigues de Moura Fernandes
dc.creatorMayra Luiza Marques da Silva
dc.creatorEvandro Ferreira da Silva
dc.creatorGilson Fernandes da Silva
dc.creatorAdriano Ribeiro de Mendonça
dc.creatorChristian Dias Cabacinha
dc.creatorEmanuel França Araújo
dc.creatorJeangelis Silva Santos
dc.creatorGiovanni Correia Vieira
dc.date.accessioned2022-07-14T12:20:39Z
dc.date.accessioned2025-09-08T23:58:43Z
dc.date.available2022-07-14T12:20:39Z
dc.date.issued2019
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.description.sponsorshipOutra Agência
dc.identifier.doihttps://doi.org/10.1016/j.jenvman.2019.109368
dc.identifier.issn0301-4797
dc.identifier.urihttps://hdl.handle.net/1843/43256
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofJournal of Environmental Management
dc.rightsAcesso Aberto
dc.subjectPlantas dos cerrados
dc.subjectInteligência artificial
dc.subjectFlorestas -- Administração
dc.subjectMáquinas
dc.titleComputational techniques applied to volume and biomass estimation of trees in brazilian savanna
dc.typeArtigo de periódico
local.citation.epage12
local.citation.issue1
local.citation.spage1
local.citation.volume249
local.description.resumoThe Brazilian Savannah, known as Cerrado, has the richest flora in the world among the savannas, with a high degree of endemic species. Despite the global ecological importance of the Cerrado, there are few studies focused on the modeling of the volume and biomass of this forest formation. Volume and biomass estimation can be performed using allometric models, artificial intelligence (AI) techniques and mixed regression models. Thus, the aim of this work was to evaluate the use of AI techniques and mixed models to estimate the volume and biomass of individual trees in vegetation of Brazilian central savanna. Numerical variables (diameter at height of 1.30 m of ground, total height, volume and biomass) and categorical variables (species) were used for the training and fitting of AI techniques and mixed models, respectively. The statistical indicators used to evaluate the training and the adjustment were the correlation coefficient, bias and Root mean square error relative. In addition, graphs were elaborated as complementary analysis. The results obtained by the statistical indicators and the graphical analysis show the great potential of AI techniques and mixed models in the estimation of volume and biomass of individual trees in Brazilian savanna vegetation. In addition, the proposed methodologies can be adapted to other biomes, forest typologies and variables of interest.
local.identifier.orcidhttps://orcid.org/0000-0002-8148-083X
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S0301479719310771

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