Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Almeida, Milena Viviane Vieira de
Orientador(a): Fernandes, Milton Marques
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Pós-Graduação em Desenvolvimento e Meio Ambiente
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://ri.ufs.br/jspui/handle/riufs/20498
Resumo: Deforestation for agriculture and livestock in the Atlantic Forest biome is the main generator of disturbed and/or degraded areas, and it is necessary to monitor them continuously. The problem is to reconcile a method of data collection, in areas of restoration, that is efficient, fast and with proven cost-benefit. The monitoring, whether of degraded areas or under restoration, usually used in different phases of degraded areas recovery plans (PRADs), allows to visualize the indicators/results obtained in comparison with the established goals, either by global agreements, protocols, or PRADs. However, in terms of space-time and costs, field campaigns become very costly. As an alternative to traditional inventories, 3D remote sensing data, such as Light Detection and Ranging (LiDAR), have been used to assist in monitoring these areas. Because LiDAR has a high cost when compared to inventory methods performed in the field, a low-cost technology, such as 3D point clouds of digital aerial photogrammetry (FAD) obtained via remotely piloted aircraft (RPA) has been improved. It is intended, therefore, with this research, to perform the (i) characterization of the vertical structure and cover and (ii) estimation of above-ground biomass (AGB) with 3D point clouds obtained by FAD-RPA in restored Atlantic Forest areas. These areas were grouped according to the restoration method: RAM (active restoration), RAR (active restoration intercropped with eucalyptus) and RPA (passive restoration). A total of 1,797 tree individuals were inventoried, distributed in 59 species and 26 families. Among the three restoration models, RAR presented the highest values of NA, H, AB and AGB. The areas under restoration that presented the highest floristic similarity (55%) were RAR and RPA. The numerical model of the terrain overestimated the elevation values of the terrain, with RMSE 1.5 m (3%) and a bias of - 0.7 m, (1.3%). On the other hand, the dominant height values of the trees of the plots were underestimated by 1 m (bias of 11.7%), with an error of 2.3 m (RMSE of 25.8%). It was possible to characterize and differentiate (group) the restoration systems analyzed with the height and coverage metrics of the FAD-RPA point cloud. The adjusted regression model showed good performance, with R2 values of 0.84 and RMSE of 11.1 Mg.ha-1 (39.2%). In the validation, R2 was 0.75 and the RMSE at the plot level was 13.0 Mg.ha-1 (46%). We can conclude that, despite overestimating the elevation values of the terrain and, consequently, underestimating the heights of the trees, the FAD-RPA data can be used to characterize the different restoration systems analyzed and to estimate the AGB values with satisfactory accuracy.
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spelling Almeida, Milena Viviane Vieira deFernandes, Milton MarquesAlmeida, André Quintão de2024-11-25T19:52:58Z2024-11-25T19:52:58Z2023-08-30ALMEIDA, Milena Viviane Vieira de. Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital. 2023. 70 f. Dissertação (Mestrado em Desenvolvimento e Meio Ambiente) – Universidade Federal de Sergipe, São Cristóvão, 2023.https://ri.ufs.br/jspui/handle/riufs/20498Deforestation for agriculture and livestock in the Atlantic Forest biome is the main generator of disturbed and/or degraded areas, and it is necessary to monitor them continuously. The problem is to reconcile a method of data collection, in areas of restoration, that is efficient, fast and with proven cost-benefit. The monitoring, whether of degraded areas or under restoration, usually used in different phases of degraded areas recovery plans (PRADs), allows to visualize the indicators/results obtained in comparison with the established goals, either by global agreements, protocols, or PRADs. However, in terms of space-time and costs, field campaigns become very costly. As an alternative to traditional inventories, 3D remote sensing data, such as Light Detection and Ranging (LiDAR), have been used to assist in monitoring these areas. Because LiDAR has a high cost when compared to inventory methods performed in the field, a low-cost technology, such as 3D point clouds of digital aerial photogrammetry (FAD) obtained via remotely piloted aircraft (RPA) has been improved. It is intended, therefore, with this research, to perform the (i) characterization of the vertical structure and cover and (ii) estimation of above-ground biomass (AGB) with 3D point clouds obtained by FAD-RPA in restored Atlantic Forest areas. These areas were grouped according to the restoration method: RAM (active restoration), RAR (active restoration intercropped with eucalyptus) and RPA (passive restoration). A total of 1,797 tree individuals were inventoried, distributed in 59 species and 26 families. Among the three restoration models, RAR presented the highest values of NA, H, AB and AGB. The areas under restoration that presented the highest floristic similarity (55%) were RAR and RPA. The numerical model of the terrain overestimated the elevation values of the terrain, with RMSE 1.5 m (3%) and a bias of - 0.7 m, (1.3%). On the other hand, the dominant height values of the trees of the plots were underestimated by 1 m (bias of 11.7%), with an error of 2.3 m (RMSE of 25.8%). It was possible to characterize and differentiate (group) the restoration systems analyzed with the height and coverage metrics of the FAD-RPA point cloud. The adjusted regression model showed good performance, with R2 values of 0.84 and RMSE of 11.1 Mg.ha-1 (39.2%). In the validation, R2 was 0.75 and the RMSE at the plot level was 13.0 Mg.ha-1 (46%). We can conclude that, despite overestimating the elevation values of the terrain and, consequently, underestimating the heights of the trees, the FAD-RPA data can be used to characterize the different restoration systems analyzed and to estimate the AGB values with satisfactory accuracy.Os desmatamentos para agricultura e pecuária no bioma Mata Atlântica são os principais geradores de áreas perturbadas e/ou degradadas, sendo necessário monitorá-los continuamente. A problemática consiste em conciliar um método de coleta de dados, em áreas de restauração, que seja eficiente, célere e com comprovado custo-benefício. O monitoramento, seja de áreas degradadas ou em restauração, normalmente utilizados em diferentes fases de planos de recuperação de áreas degradadas (PRADs), permite visualizar os indicadores/resultados obtidos em comparação com as metas estabelecidas, seja por acordos globais, protocolos ou PRADs. No entanto, nos quesitos espaço-tempo e custos, as campanhas de campo tornam-se muito onerosas. Como alternativa aos inventários tradicionais, dados de sensoriamento remoto 3D, como Light Detection and Ranging (LiDAR), vêm sendo utilizados para auxiliar no monitoramento dessas áreas. Devido ao LiDAR possuir elevado custo quando comparado aos métodos de inventário realizados em campo, uma tecnologia de baixo custo, como as nuvens de pontos 3D de fotogrametria aérea digital (FAD) obtidas via aeronave remotamente pilotada (RPA) vem sendo aprimorada. Pretende-se, portanto, com esta pesquisa, realizar a (i) caracterização da estrutura vertical e de cobertura e (ii) estimativa de biomassa acima do solo (AGB) com nuvens de pontos 3D obtidas por FAD-RPA em áreas de Mata Atlântica restauradas. Essas áreas foram agrupadas de acordo com o método de restauração: RAM (restauração ativa), RAR (restauração ativa consorciada com eucalipto) e RPA (restauração passiva). Foram inventariados 1.797 indivíduos arbóreos, distribuídos em 59 espécies e 26 famílias. Dentre os três modelos de restauração estudados, a RAR apresentou os maiores valores de NA, H, AB e AGB. As áreas em restauração que apresentaram maior similaridade florística (55%) foram RAR e RPA. O modelo numérico do terreno superestimou os valores de elevação do terreno, com RMSE 1,5 m (3%) e um viés de -0,7 m, (1,3%). Já os valores de altura dominante das árvores das parcelas, foram subestimados em 1 m (viés de 11,7%), com um erro de 2,3 m (RMSE de 25,8%). Foi possível caracterizar e diferenciar (agrupar) os sistemas de restauração analisados com as métricas de altura e de cobertura da nuvem de pontos FAD-RPA. O modelo de regressão ajustado apresentou bom desempenho, com valores de R2 de 0,84 e o RMSE de 11,1 Mg.ha-1 (39,2%). Na validação, R2 foi de 0,75 e o RMSE ao nível de parcela de 13,0 Mg.ha−1 (46%). Podemos concluir que, apesar de superestimar os valores de elevação do terreno e, consequentemente, subestimar as alturas das árvores, os dados de FAD-RPA podem ser utilizados para caracterizar os diferentes sistemas de restauração analisados e estimar os valores de AGB com acurácia satisfatória.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESSão CristóvãoporMeio ambienteBiomas (Mata Atlântica)Agricultura (aspectos ambientais)PecuáriaDegradação ambientalSensoriamento remotoDroneAeronave remotamente pilotadaBiomassa acima do soloNordeste do BrasilSergipeRemotely piloted aircraftAbove-ground biomassNortheast of BrazilOUTROSEstimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digitalinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPós-Graduação em Desenvolvimento e Meio AmbienteUniversidade Federal de Sergipe (UFS)reponame:Repositório Institucional da UFSinstname:Universidade Federal de Sergipe (UFS)instacron:UFSinfo:eu-repo/semantics/openAccessLICENSElicense.txtlicense.txttext/plain; charset=utf-81475https://ri.ufs.br/jspui/bitstream/riufs/20498/1/license.txt098cbbf65c2c15e1fb2e49c5d306a44cMD51ORIGINALMILENA_VIVIANE_VIEIRA_ALMEIDA.pdfMILENA_VIVIANE_VIEIRA_ALMEIDA.pdfapplication/pdf1958879https://ri.ufs.br/jspui/bitstream/riufs/20498/2/MILENA_VIVIANE_VIEIRA_ALMEIDA.pdfb86000feb1ef80861fdb1411a4e64652MD52riufs/204982025-01-09 11:31:54.207oai:oai:ri.ufs.br:repo_01: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Repositório InstitucionalPUBhttps://ri.ufs.br/oai/requestrepositorio@academico.ufs.bropendoar:2025-01-09T14:31:54Repositório Institucional da UFS - Universidade Federal de Sergipe (UFS)false
dc.title.pt_BR.fl_str_mv Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
title Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
spellingShingle Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
Almeida, Milena Viviane Vieira de
Meio ambiente
Biomas (Mata Atlântica)
Agricultura (aspectos ambientais)
Pecuária
Degradação ambiental
Sensoriamento remoto
Drone
Aeronave remotamente pilotada
Biomassa acima do solo
Nordeste do Brasil
Sergipe
Remotely piloted aircraft
Above-ground biomass
Northeast of Brazil
OUTROS
title_short Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
title_full Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
title_fullStr Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
title_full_unstemmed Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
title_sort Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital
author Almeida, Milena Viviane Vieira de
author_facet Almeida, Milena Viviane Vieira de
author_role author
dc.contributor.author.fl_str_mv Almeida, Milena Viviane Vieira de
dc.contributor.advisor1.fl_str_mv Fernandes, Milton Marques
dc.contributor.advisor-co1.fl_str_mv Almeida, André Quintão de
contributor_str_mv Fernandes, Milton Marques
Almeida, André Quintão de
dc.subject.por.fl_str_mv Meio ambiente
Biomas (Mata Atlântica)
Agricultura (aspectos ambientais)
Pecuária
Degradação ambiental
Sensoriamento remoto
Drone
Aeronave remotamente pilotada
Biomassa acima do solo
Nordeste do Brasil
Sergipe
topic Meio ambiente
Biomas (Mata Atlântica)
Agricultura (aspectos ambientais)
Pecuária
Degradação ambiental
Sensoriamento remoto
Drone
Aeronave remotamente pilotada
Biomassa acima do solo
Nordeste do Brasil
Sergipe
Remotely piloted aircraft
Above-ground biomass
Northeast of Brazil
OUTROS
dc.subject.eng.fl_str_mv Remotely piloted aircraft
Above-ground biomass
Northeast of Brazil
dc.subject.cnpq.fl_str_mv OUTROS
description Deforestation for agriculture and livestock in the Atlantic Forest biome is the main generator of disturbed and/or degraded areas, and it is necessary to monitor them continuously. The problem is to reconcile a method of data collection, in areas of restoration, that is efficient, fast and with proven cost-benefit. The monitoring, whether of degraded areas or under restoration, usually used in different phases of degraded areas recovery plans (PRADs), allows to visualize the indicators/results obtained in comparison with the established goals, either by global agreements, protocols, or PRADs. However, in terms of space-time and costs, field campaigns become very costly. As an alternative to traditional inventories, 3D remote sensing data, such as Light Detection and Ranging (LiDAR), have been used to assist in monitoring these areas. Because LiDAR has a high cost when compared to inventory methods performed in the field, a low-cost technology, such as 3D point clouds of digital aerial photogrammetry (FAD) obtained via remotely piloted aircraft (RPA) has been improved. It is intended, therefore, with this research, to perform the (i) characterization of the vertical structure and cover and (ii) estimation of above-ground biomass (AGB) with 3D point clouds obtained by FAD-RPA in restored Atlantic Forest areas. These areas were grouped according to the restoration method: RAM (active restoration), RAR (active restoration intercropped with eucalyptus) and RPA (passive restoration). A total of 1,797 tree individuals were inventoried, distributed in 59 species and 26 families. Among the three restoration models, RAR presented the highest values of NA, H, AB and AGB. The areas under restoration that presented the highest floristic similarity (55%) were RAR and RPA. The numerical model of the terrain overestimated the elevation values of the terrain, with RMSE 1.5 m (3%) and a bias of - 0.7 m, (1.3%). On the other hand, the dominant height values of the trees of the plots were underestimated by 1 m (bias of 11.7%), with an error of 2.3 m (RMSE of 25.8%). It was possible to characterize and differentiate (group) the restoration systems analyzed with the height and coverage metrics of the FAD-RPA point cloud. The adjusted regression model showed good performance, with R2 values of 0.84 and RMSE of 11.1 Mg.ha-1 (39.2%). In the validation, R2 was 0.75 and the RMSE at the plot level was 13.0 Mg.ha-1 (46%). We can conclude that, despite overestimating the elevation values of the terrain and, consequently, underestimating the heights of the trees, the FAD-RPA data can be used to characterize the different restoration systems analyzed and to estimate the AGB values with satisfactory accuracy.
publishDate 2023
dc.date.issued.fl_str_mv 2023-08-30
dc.date.accessioned.fl_str_mv 2024-11-25T19:52:58Z
dc.date.available.fl_str_mv 2024-11-25T19:52:58Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv ALMEIDA, Milena Viviane Vieira de. Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital. 2023. 70 f. Dissertação (Mestrado em Desenvolvimento e Meio Ambiente) – Universidade Federal de Sergipe, São Cristóvão, 2023.
dc.identifier.uri.fl_str_mv https://ri.ufs.br/jspui/handle/riufs/20498
identifier_str_mv ALMEIDA, Milena Viviane Vieira de. Estimação de biomassa e caracterização estrutural de áreas restauradas da Mata Atlântica com dados 3D obtidos por fotogrametria aérea digital. 2023. 70 f. Dissertação (Mestrado em Desenvolvimento e Meio Ambiente) – Universidade Federal de Sergipe, São Cristóvão, 2023.
url https://ri.ufs.br/jspui/handle/riufs/20498
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dc.publisher.program.fl_str_mv Pós-Graduação em Desenvolvimento e Meio Ambiente
dc.publisher.initials.fl_str_mv Universidade Federal de Sergipe (UFS)
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instname_str Universidade Federal de Sergipe (UFS)
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institution UFS
reponame_str Repositório Institucional da UFS
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