LiDAR based Biomass Estimation System for Forested Areas

Detalhes bibliográficos
Autor(a) principal: Simões, Luís Filipe Rosa
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/126160
Resumo: In continental Portugal, forest fires are considered the biggest and most serious cause of forest deterioration and therefore the introduction of forest management mechanisms and biomass monitoring are imperative for a better future. However, conducting field studies on a large scale is a very expensive and time-consuming task. Alternatively, through remote sensing via a LiDAR, it becomes possible to map, with high accuracy, forest parameters such as tree height, diameter at breast height or tree canopy length in order to carry out other relevant estimates such as above ground biomass. In this sense, this dissertation aims to develop a system capable of, through algorithms and filters of point cloud processing, as statistical outlier removal, progressive morphological filters and region growing segmentation, extract in detail,a digital terrain model and correctly detect the number of trees in a given area, proceeding to the measurement of some interesting variables from the point of view of a forest inventory. Thus, testing data of different characteristics, our detection method obtained positive results, with all the average detection rates above 80 %.
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spelling LiDAR based Biomass Estimation System for Forested AreasUAVLiDARairborne remote sensingwildfiresbiomassforestDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaIn continental Portugal, forest fires are considered the biggest and most serious cause of forest deterioration and therefore the introduction of forest management mechanisms and biomass monitoring are imperative for a better future. However, conducting field studies on a large scale is a very expensive and time-consuming task. Alternatively, through remote sensing via a LiDAR, it becomes possible to map, with high accuracy, forest parameters such as tree height, diameter at breast height or tree canopy length in order to carry out other relevant estimates such as above ground biomass. In this sense, this dissertation aims to develop a system capable of, through algorithms and filters of point cloud processing, as statistical outlier removal, progressive morphological filters and region growing segmentation, extract in detail,a digital terrain model and correctly detect the number of trees in a given area, proceeding to the measurement of some interesting variables from the point of view of a forest inventory. Thus, testing data of different characteristics, our detection method obtained positive results, with all the average detection rates above 80 %.Em Portugal continental, os incêndios florestais são considerados a maior e mais grave causa de deterioramento da floresta e por isso a introdução de mecanismos de gestão florestal e monitorização da biomassa são imperativos para um futuro melhor. No entanto, realizar estudos de campo em grande escala é uma tarefa muito dispendiosa e demorosa. Em alternativa, através da deteção remota por vias de um LiDAR torna-se possível mapear, com elevado rigor, parâmetros florestais como altura das arvores, diâmetro do tronco ou comprimento da copa da arvore de modo a proceder a outras relevantes estimações como a biomassa. Neste sentido, esta dissertação teve como objetivo o desenvolvimento de um sistema capaz de, através de algoritmos e filtros de processamento de nuvens de pontos, como remoção de outliers estatístico, filtros morfologicos progressivos e segmentação por crescimento de regiões anexas , extrair com detalhe, um modelo digital do terreno e detetar corretamente o número de arvores numa determinada área, procedendo à medição de algumas variáveis interessantes do ponto de vista do inventário florestal. Assim, testando dados de diferentes características, o nosso método de deteção obteve resultados positivos, com todas as taxas deteção média superiores a 80 %.Oliveira, JoséMarques, FranciscoRUNSimões, Luís Filipe Rosa2021-10-15T10:29:28Z2021-022021-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/126160enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:06:36Zoai:run.unl.pt:10362/126160Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:45:47.249566Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv LiDAR based Biomass Estimation System for Forested Areas
title LiDAR based Biomass Estimation System for Forested Areas
spellingShingle LiDAR based Biomass Estimation System for Forested Areas
Simões, Luís Filipe Rosa
UAV
LiDAR
airborne remote sensing
wildfires
biomass
forest
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short LiDAR based Biomass Estimation System for Forested Areas
title_full LiDAR based Biomass Estimation System for Forested Areas
title_fullStr LiDAR based Biomass Estimation System for Forested Areas
title_full_unstemmed LiDAR based Biomass Estimation System for Forested Areas
title_sort LiDAR based Biomass Estimation System for Forested Areas
author Simões, Luís Filipe Rosa
author_facet Simões, Luís Filipe Rosa
author_role author
dc.contributor.none.fl_str_mv Oliveira, José
Marques, Francisco
RUN
dc.contributor.author.fl_str_mv Simões, Luís Filipe Rosa
dc.subject.por.fl_str_mv UAV
LiDAR
airborne remote sensing
wildfires
biomass
forest
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic UAV
LiDAR
airborne remote sensing
wildfires
biomass
forest
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description In continental Portugal, forest fires are considered the biggest and most serious cause of forest deterioration and therefore the introduction of forest management mechanisms and biomass monitoring are imperative for a better future. However, conducting field studies on a large scale is a very expensive and time-consuming task. Alternatively, through remote sensing via a LiDAR, it becomes possible to map, with high accuracy, forest parameters such as tree height, diameter at breast height or tree canopy length in order to carry out other relevant estimates such as above ground biomass. In this sense, this dissertation aims to develop a system capable of, through algorithms and filters of point cloud processing, as statistical outlier removal, progressive morphological filters and region growing segmentation, extract in detail,a digital terrain model and correctly detect the number of trees in a given area, proceeding to the measurement of some interesting variables from the point of view of a forest inventory. Thus, testing data of different characteristics, our detection method obtained positive results, with all the average detection rates above 80 %.
publishDate 2021
dc.date.none.fl_str_mv 2021-10-15T10:29:28Z
2021-02
2021-02-01T00:00:00Z
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 http://hdl.handle.net/10362/126160
url http://hdl.handle.net/10362/126160
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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