LiDAR based Biomass Estimation System for Forested Areas
Autor(a) principal: | |
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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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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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1799138062150664192 |