Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/10816 |
Resumo: | Currently, the emphasis given to the climatic issues is due to the pronounced increase in the concentrations of carbon dioxide in the atmosphere and its effects over the environment. Among the many environmental services provided by forests, we highlight the sequestering and stocking of carbon. Forest plantations with eucalyptus species represent 5.5 million hectares in Brazil. These species are characterized by the rapid growth and consequent speed in absorbing and capturing carbon available in the atmosphere. The quantification of the carbon stock in the forest biomass is a laborious, time-consuming and onerous activity. New technologies have been developed in order to remedy such limitations, among which is the LiDAR (Light Direction and Raning) technology. The precision of the surveys using LiDAR depends on the traits intrinsic to the system (sensor, point density, flight platform altitude, pulse frequency, footprint, scanning angle, among others). The estimation of biomass and carbon stock obtained from the LiDAR occur via modeling by means of parametric (multiple linear regression) or non-parametric (Random Forest) methods. In this context, the objective of this work was to evaluate the use of LiDAR metrics in the estimation of the carbon stock of Eucalyptus spp plantations, as well as to study the influence of the flight traits and type of modeling. We conducted two LiDAR flights over eight farms owned by the Fibria company. With the cloud of points derived from each flight, we obtained the LiDAR metrics, which were pre-selected according to the correlation with the carbon stock and multicollinearity between them, resulting in six independent variables that comprised the model. The dependent variable of carbon stock was obtained by means of the Schumacher & Hall logarithm model (1993) adapted for the study area. We adjusted models from flight 1 via multiple linear regression (1), flight 2 via multiple regression (2), flight 1 via Random Forest (3) and flight 2 via Random Forest (4). The best models of 1, 2, 3 and 4 obtained R2 ajd of 83%, 84%, 82% and 79%, and RMSE of 7.82, 7.71, 8.02 and 8.72 Mg ha-1 , respectively. In all cases, the independent variables comprising the final models were hp50 and stratum VI. Therefore, with the LiDAR metrics, it is possible to obtaine accurate estimates of the carbon stocks in Eucalyptus planted forests. There was no significant difference between the carbon stock estimates obtained from flights 1 and 2, as well as between those obtained from modeling via multiple linear regression and Random Forest. |
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Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDARCarbon stock the estimate in Eucalyptus plantations spp. from LiDAR metricsBiomassa florestalTecnologia laser aerotransportadaRegressão linear múltiplaRandom forestForest biomassAirborne laser technologyMultiple linear regressionRandom forestManejo FlorestalCurrently, the emphasis given to the climatic issues is due to the pronounced increase in the concentrations of carbon dioxide in the atmosphere and its effects over the environment. Among the many environmental services provided by forests, we highlight the sequestering and stocking of carbon. Forest plantations with eucalyptus species represent 5.5 million hectares in Brazil. These species are characterized by the rapid growth and consequent speed in absorbing and capturing carbon available in the atmosphere. The quantification of the carbon stock in the forest biomass is a laborious, time-consuming and onerous activity. New technologies have been developed in order to remedy such limitations, among which is the LiDAR (Light Direction and Raning) technology. The precision of the surveys using LiDAR depends on the traits intrinsic to the system (sensor, point density, flight platform altitude, pulse frequency, footprint, scanning angle, among others). The estimation of biomass and carbon stock obtained from the LiDAR occur via modeling by means of parametric (multiple linear regression) or non-parametric (Random Forest) methods. In this context, the objective of this work was to evaluate the use of LiDAR metrics in the estimation of the carbon stock of Eucalyptus spp plantations, as well as to study the influence of the flight traits and type of modeling. We conducted two LiDAR flights over eight farms owned by the Fibria company. With the cloud of points derived from each flight, we obtained the LiDAR metrics, which were pre-selected according to the correlation with the carbon stock and multicollinearity between them, resulting in six independent variables that comprised the model. The dependent variable of carbon stock was obtained by means of the Schumacher & Hall logarithm model (1993) adapted for the study area. We adjusted models from flight 1 via multiple linear regression (1), flight 2 via multiple regression (2), flight 1 via Random Forest (3) and flight 2 via Random Forest (4). The best models of 1, 2, 3 and 4 obtained R2 ajd of 83%, 84%, 82% and 79%, and RMSE of 7.82, 7.71, 8.02 and 8.72 Mg ha-1 , respectively. In all cases, the independent variables comprising the final models were hp50 and stratum VI. Therefore, with the LiDAR metrics, it is possible to obtaine accurate estimates of the carbon stocks in Eucalyptus planted forests. There was no significant difference between the carbon stock estimates obtained from flights 1 and 2, as well as between those obtained from modeling via multiple linear regression and Random Forest.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Atualmente o destaque dado às questões climáticas se deve ao aumento acentuado das concentrações de dióxido de carbono na atmosfera e seu efeito sobre o ambiente. Dentre os diversos serviços ambientais prestados pelas florestas, destacam-se o sequestro e estocagem de carbono. Plantios florestais com espécies de eucalipto no Brasil representam 5,5 milhões de hectares. Essas espécies se caracterizam pelo rápido crescimento e consequente rapidez em absorver e capturar carbono disponível na atmosfera em biomassa. A quantificação do estoque de carbono na biomassa florestal é uma atividade trabalhosa, demorada e onerosa e novas tecnologias vêm sendo desenvolvidas a fim de sanar tais limitações, dentre estas, a tecnologia LiDAR (Light Detection and Raning). A precisão dos levantamentos, utilizando LiDAR, depende das características intrínsecas ao sistema (sensor, densidade de pontos, altitude da plataforma de voo, frequência dos pulsos, footprint, ângulo de varredura, entre outros). Estimativas da biomassa e estoque de carbono, com base nos dados LiDAR, ocorrem via modelagem por métodos paramétricos (regressão linear múltipla) ou não paramétricos (Random Forest). Neste contexto, objetivou-se neste trabalho avaliar o uso das métricas LiDAR na estimativa do estoque de carbono em plantios de Eucalyptus spp, bem como o estudo das influências das características do voo e do tipo de modelagem. Foram realizados dois voos LiDAR em oito fazendas da empresa Fibria. A partir da nuvem de pontos, provenientes de cada voo, obtiveram-se as métricas LiDAR que foram pré- selecionadas quanto à correlação com o estoque de carbono e multicolinearidade entre elas, resultando em seis variáveis independentes que compuseram o modelo. A variável dependente estoque de carbono foi obtida por intermédio do modelo logaritmizado de Schumacher e Hall (1993) adaptado para a área de estudo. Ajustaram-se modelos com base no voo 1 via regressão linear múltipla (1), voo 2 via regressão linear múltipla (2), voo 1 via Random Forest (3) e voo 2 via Random Forest (4). Os melhores modelos de 1, 2, 3 e 4 obtiveram R2 ajd 83%, 84%, 82% e 79% e RMSE 7,82; 7,71; 8,02; 8,72 Mg ha-1 , respectivamente. Em todos os casos, as variáveis independentes que compuseram os modelos finais foram hp50 e stratum VI. Portanto, a partir das métricas LiDAR é possível se obter estimativas acuradas do estoque de carbono em florestas plantadas de eucalipto. Não houve diferenças significativas entre as estimativas do estoque de carbono provenientes dos voos 1 e 2, bem como entre as estimativas do estoque de carbono obtidas por modelagem via regressão linear múltipla e random forest.Universidade Federal de LavrasPrograma de Pós-Graduação em Engenharia FlorestalUFLAbrasilDepartamento de Ciências FlorestaisCarvalho, Luis Marcelo Tavares deVolpato, Margarete Marin LordeloFerraz Filho, Antonio CarlosNunes, Ana Carolina Magalhães2016-01-29T16:34:30Z2016-01-29T16:34:30Z2016-01-292015-07-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfNUNES, A. C. M. Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR. 2015. 70 p. Dissertação (Mestrado em Engenharia Florestal)-Universidade Federal de Lavras, Lavras, 2015.http://repositorio.ufla.br/jspui/handle/1/10816porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLA2023-05-11T12:22:35Zoai:localhost:1/10816Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-11T12:22:35Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR Carbon stock the estimate in Eucalyptus plantations spp. from LiDAR metrics |
title |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR |
spellingShingle |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR Nunes, Ana Carolina Magalhães Biomassa florestal Tecnologia laser aerotransportada Regressão linear múltipla Random forest Forest biomass Airborne laser technology Multiple linear regression Random forest Manejo Florestal |
title_short |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR |
title_full |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR |
title_fullStr |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR |
title_full_unstemmed |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR |
title_sort |
Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR |
author |
Nunes, Ana Carolina Magalhães |
author_facet |
Nunes, Ana Carolina Magalhães |
author_role |
author |
dc.contributor.none.fl_str_mv |
Carvalho, Luis Marcelo Tavares de Volpato, Margarete Marin Lordelo Ferraz Filho, Antonio Carlos |
dc.contributor.author.fl_str_mv |
Nunes, Ana Carolina Magalhães |
dc.subject.por.fl_str_mv |
Biomassa florestal Tecnologia laser aerotransportada Regressão linear múltipla Random forest Forest biomass Airborne laser technology Multiple linear regression Random forest Manejo Florestal |
topic |
Biomassa florestal Tecnologia laser aerotransportada Regressão linear múltipla Random forest Forest biomass Airborne laser technology Multiple linear regression Random forest Manejo Florestal |
description |
Currently, the emphasis given to the climatic issues is due to the pronounced increase in the concentrations of carbon dioxide in the atmosphere and its effects over the environment. Among the many environmental services provided by forests, we highlight the sequestering and stocking of carbon. Forest plantations with eucalyptus species represent 5.5 million hectares in Brazil. These species are characterized by the rapid growth and consequent speed in absorbing and capturing carbon available in the atmosphere. The quantification of the carbon stock in the forest biomass is a laborious, time-consuming and onerous activity. New technologies have been developed in order to remedy such limitations, among which is the LiDAR (Light Direction and Raning) technology. The precision of the surveys using LiDAR depends on the traits intrinsic to the system (sensor, point density, flight platform altitude, pulse frequency, footprint, scanning angle, among others). The estimation of biomass and carbon stock obtained from the LiDAR occur via modeling by means of parametric (multiple linear regression) or non-parametric (Random Forest) methods. In this context, the objective of this work was to evaluate the use of LiDAR metrics in the estimation of the carbon stock of Eucalyptus spp plantations, as well as to study the influence of the flight traits and type of modeling. We conducted two LiDAR flights over eight farms owned by the Fibria company. With the cloud of points derived from each flight, we obtained the LiDAR metrics, which were pre-selected according to the correlation with the carbon stock and multicollinearity between them, resulting in six independent variables that comprised the model. The dependent variable of carbon stock was obtained by means of the Schumacher & Hall logarithm model (1993) adapted for the study area. We adjusted models from flight 1 via multiple linear regression (1), flight 2 via multiple regression (2), flight 1 via Random Forest (3) and flight 2 via Random Forest (4). The best models of 1, 2, 3 and 4 obtained R2 ajd of 83%, 84%, 82% and 79%, and RMSE of 7.82, 7.71, 8.02 and 8.72 Mg ha-1 , respectively. In all cases, the independent variables comprising the final models were hp50 and stratum VI. Therefore, with the LiDAR metrics, it is possible to obtaine accurate estimates of the carbon stocks in Eucalyptus planted forests. There was no significant difference between the carbon stock estimates obtained from flights 1 and 2, as well as between those obtained from modeling via multiple linear regression and Random Forest. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-07-07 2016-01-29T16:34:30Z 2016-01-29T16:34:30Z 2016-01-29 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
NUNES, A. C. M. Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR. 2015. 70 p. Dissertação (Mestrado em Engenharia Florestal)-Universidade Federal de Lavras, Lavras, 2015. http://repositorio.ufla.br/jspui/handle/1/10816 |
identifier_str_mv |
NUNES, A. C. M. Estimativa do estoque de carbono em plantios de Eucalyptus spp. a partir de métricas LiDAR. 2015. 70 p. Dissertação (Mestrado em Engenharia Florestal)-Universidade Federal de Lavras, Lavras, 2015. |
url |
http://repositorio.ufla.br/jspui/handle/1/10816 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Lavras Programa de Pós-Graduação em Engenharia Florestal UFLA brasil Departamento de Ciências Florestais |
publisher.none.fl_str_mv |
Universidade Federal de Lavras Programa de Pós-Graduação em Engenharia Florestal UFLA brasil Departamento de Ciências Florestais |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
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UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
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Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
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1807835136572522496 |