Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS
Ano de defesa: | 2022 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
Centro de Ciências Rurais |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Florestal
|
Departamento: |
Recursos Florestais e Engenharia Florestal
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/24178 |
Resumo: | The diagnosis of street afforestation is an essential element in urban forest planning. In this way, it becomes necessary to develop methods to obtain qualitative and quantitative variables from the trees present in cities. Therefore, the present study aims to evaluate the application of tools based on geotechnologies to characterize and obtain dendrometric variables of street afforestation in the municipality of São Pedro do Sul, RS. Initially, it started with a census of the trees on the municipality's public roads. Then, the collection of the geographic position and the popular name of all the municipality sidewalks trees occurred for this purpose. Finally, the data were tabulated in Microsoft Excel® to create a table containing the individual's family, scientific name, and geographic position. After that, the aerial images collection happened in randomly selected streets, using the Remotely Piloted Aircraft System (RPAS) model Phantom 4 Pro®. Pix4D Mapper® software generated the following data: Orthophotomosaic, Digital Surface Model (MDS). The computer application QGIS version 3.10 generated the Digital Elevation Model (DEM) and collected data on the trees' height and their respective canopy area through photo interpretation. The Meanshift algorithm present in the ArcGIS Pro® computer application performed the automatic segmentation of the crowns. The height and canopy data inventory comparison happened using the conventional method and image analysis. RStudio software version 4.1.0 performed the data comparison and descriptive analysis. Data were validated using linear regression analysis, and the models were compared using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results indicate that using geotechnologies and field data allowed municipal street trees' spatial and diversity characterization. Regarding the variables analyzed, the methods showed no significant difference for the Meliaceae family (p-value > 0.05) and for the species Handroanthus chrysotrichus and Melia azedarach, (pvalue > 0.05). In addition, Fabaceae and Bignoneaceae families had a higher average height than the other families. The canopy area values were higher for the conventional method (p-value < 0.05), differing from the other methods. Automatic segmentation showed no significant difference compared to photo interpretation (p-value > 0.05). The conclusion says that the use of geotechnologies helps diagnose the urban forest, enabling spatial characterization and obtaining essential quantitative variables for planning. In addition, the use of data obtained by RPAS and image processing techniques are rapidly and constantly expanding, demonstrating efficiency and potential for use in road afforestation management. |
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2022-04-25T15:44:11Z2022-04-25T15:44:11Z2022-03-07http://repositorio.ufsm.br/handle/1/24178The diagnosis of street afforestation is an essential element in urban forest planning. In this way, it becomes necessary to develop methods to obtain qualitative and quantitative variables from the trees present in cities. Therefore, the present study aims to evaluate the application of tools based on geotechnologies to characterize and obtain dendrometric variables of street afforestation in the municipality of São Pedro do Sul, RS. Initially, it started with a census of the trees on the municipality's public roads. Then, the collection of the geographic position and the popular name of all the municipality sidewalks trees occurred for this purpose. Finally, the data were tabulated in Microsoft Excel® to create a table containing the individual's family, scientific name, and geographic position. After that, the aerial images collection happened in randomly selected streets, using the Remotely Piloted Aircraft System (RPAS) model Phantom 4 Pro®. Pix4D Mapper® software generated the following data: Orthophotomosaic, Digital Surface Model (MDS). The computer application QGIS version 3.10 generated the Digital Elevation Model (DEM) and collected data on the trees' height and their respective canopy area through photo interpretation. The Meanshift algorithm present in the ArcGIS Pro® computer application performed the automatic segmentation of the crowns. The height and canopy data inventory comparison happened using the conventional method and image analysis. RStudio software version 4.1.0 performed the data comparison and descriptive analysis. Data were validated using linear regression analysis, and the models were compared using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results indicate that using geotechnologies and field data allowed municipal street trees' spatial and diversity characterization. Regarding the variables analyzed, the methods showed no significant difference for the Meliaceae family (p-value > 0.05) and for the species Handroanthus chrysotrichus and Melia azedarach, (pvalue > 0.05). In addition, Fabaceae and Bignoneaceae families had a higher average height than the other families. The canopy area values were higher for the conventional method (p-value < 0.05), differing from the other methods. Automatic segmentation showed no significant difference compared to photo interpretation (p-value > 0.05). The conclusion says that the use of geotechnologies helps diagnose the urban forest, enabling spatial characterization and obtaining essential quantitative variables for planning. In addition, the use of data obtained by RPAS and image processing techniques are rapidly and constantly expanding, demonstrating efficiency and potential for use in road afforestation management.O diagnóstico da arborização viária é um elemento essencial no planejamento da floresta urbana. Desta maneira, torna-se necessário o desenvolvimento de métodos para a obtenção de variáveis qualitativas e quantitativas das árvores presentes nas cidades. Portanto, o presente estudo tem por objetivo avaliar a aplicação de ferramentas baseadas em geotecnologias para a caracterização e obtenção de variáveis dendrométricas da arborização viária no município de São Pedro do Sul, RS. De modo inicial, realizou-se um censo dos indivíduos arbóreos presente nas vias públicas do município, para tal, coletou-se a posição geográfica e o respectivo nome popular de todas as árvores presentes nas calçadas do município. Os dados foram tabulados no Microsoft Excel® para a criação de uma tabela contendo a família, nome científico e posição geográfica do indivíduo. Feito isso, sortearam-se algumas ruas do município para a coleta de imagens aéreas com a utilização do Remotely Piloted Aircraft System (RPAS, em português, Sistema de Aeronave Remotamente Pilotada) modelo Phantom 4 Pro®. Utilizou-se o software Pix4D Mapper® para gerar os seguintes dados: Ortofotomosaico, Modelo Digital de Superfíce (MDS). Utilizou-se o aplicativo computacional QGIS versão 3.10 para a geração do Modelo Digital de Elevação (MDE) e coleta dos dados de altura das árvores, assim como sua respectiva área de copa por meio da fotointerpretação. Para a segmentação automática das copas, utilizou-se o algoritmo Meanshift presente no aplicativo computacional ArcGIS Pro®. Realizou-se a comparação dos dados obtidos para altura e área de copa, comparando-se o inventário pelo método convencional e análise de imagem. A comparação dos dados e análise descritiva foram realizadas no software RStudio versão 4.1.0. Os dados foram validados por meio de análise de regressão linear e os modelos foram comparados a partir da Raiz do Erro Quadrático Médio (RMSE) e Erro Médio Absoluto (MAE). Os resultados indicam que a utilização de geotecnologias em conjunto com os dados de campo permitiu a caracterização espacial e de diversidade da arborização viária municipal. Em relação às variáveis analisadas, observou-se que os métodos não apresentaram diferença significativa para a família Meliaceae (p-valor > 0,05) e para as espécies Handroanthus chrysotrichus e Melia azedarach, (p-valor > 0,05). Além disso, famílias Fabaceae e Bignoneaceae apresentaram altura média superior às demais famílias. Os valores de área de copa foram superiores para o método convencional (p-valor < 0,05), diferindo dos demais métodos. A segmentação automática não apresentou diferença significativa em comparação à fotointerpretação (p-valor > 0,05). Conclui-se que a utilização de geotecnologias auxilia no diagnóstico da floresta urbana, possibilitando a caracterização espacial e obtenção de variáveis quantitativas essenciais ao planejamento. Além disso, a utilização de dados obtidos por RPAS e as técnicas de processamento de imagens estão em rápida e constante expansão, demonstrando eficiência e potencial de uso na gestão da arborização viária.porUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em Engenharia FlorestalUFSMBrasilRecursos Florestais e Engenharia FlorestalAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessRPASSensoriamento remotoInventário florestalArborização urbanaPlanejamento urbanoRemote sensingInventory afforestationUrban planningCNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTALUso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RSUse and application of geotechnologies for the study of public road arborization in the municipality of São Pedro do Sul, RSinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisEugenio, Fernando Coelhohttp://lattes.cnpq.br/2825133116316989Fortes, Fabiano de OliveiraBobrowski, RogérioSantos, Alexandre Rosa doshttp://lattes.cnpq.br/0717580930945518Felippe, Bruno Moreira5002000000036006006006006006002f95394d-f685-4a57-b880-e3e9d3415eb007598a37-9ebc-41ef-9e11-cbc0559ac333370731cb-e291-42eb-8745-50558098e49f667e35ca-4fe6-4eed-ae26-a9a7a5de3cf0fd82c9a2-53d0-48cc-8d29-20bc4dff3becreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/24178/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/24178/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53ORIGINALDIS_PPGEF_2022_FELIPPE_BRUNO.pdfDIS_PPGEF_2022_FELIPPE_BRUNO.pdfDissertação de mestradoapplication/pdf2611224http://repositorio.ufsm.br/bitstream/1/24178/1/DIS_PPGEF_2022_FELIPPE_BRUNO.pdf2ee0f74e93bdbcb4c0f449b8207fd2f2MD511/241782022-04-25 12:44:13.875oai:repositorio.ufsm.br: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ório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestopendoar:39132022-04-25T15:44:13Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
dc.title.alternative.eng.fl_str_mv |
Use and application of geotechnologies for the study of public road arborization in the municipality of São Pedro do Sul, RS |
title |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
spellingShingle |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS Felippe, Bruno Moreira RPAS Sensoriamento remoto Inventário florestal Arborização urbana Planejamento urbano Remote sensing Inventory afforestation Urban planning CNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL |
title_short |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
title_full |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
title_fullStr |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
title_full_unstemmed |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
title_sort |
Uso e aplicação de geotecnologias para estudo da arborização de vias públicas no município de São Pedro do Sul, RS |
author |
Felippe, Bruno Moreira |
author_facet |
Felippe, Bruno Moreira |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Eugenio, Fernando Coelho |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/2825133116316989 |
dc.contributor.advisor-co1.fl_str_mv |
Fortes, Fabiano de Oliveira |
dc.contributor.referee1.fl_str_mv |
Bobrowski, Rogério |
dc.contributor.referee2.fl_str_mv |
Santos, Alexandre Rosa dos |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0717580930945518 |
dc.contributor.author.fl_str_mv |
Felippe, Bruno Moreira |
contributor_str_mv |
Eugenio, Fernando Coelho Fortes, Fabiano de Oliveira Bobrowski, Rogério Santos, Alexandre Rosa dos |
dc.subject.por.fl_str_mv |
RPAS Sensoriamento remoto Inventário florestal Arborização urbana Planejamento urbano |
topic |
RPAS Sensoriamento remoto Inventário florestal Arborização urbana Planejamento urbano Remote sensing Inventory afforestation Urban planning CNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL |
dc.subject.eng.fl_str_mv |
Remote sensing Inventory afforestation Urban planning |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL |
description |
The diagnosis of street afforestation is an essential element in urban forest planning. In this way, it becomes necessary to develop methods to obtain qualitative and quantitative variables from the trees present in cities. Therefore, the present study aims to evaluate the application of tools based on geotechnologies to characterize and obtain dendrometric variables of street afforestation in the municipality of São Pedro do Sul, RS. Initially, it started with a census of the trees on the municipality's public roads. Then, the collection of the geographic position and the popular name of all the municipality sidewalks trees occurred for this purpose. Finally, the data were tabulated in Microsoft Excel® to create a table containing the individual's family, scientific name, and geographic position. After that, the aerial images collection happened in randomly selected streets, using the Remotely Piloted Aircraft System (RPAS) model Phantom 4 Pro®. Pix4D Mapper® software generated the following data: Orthophotomosaic, Digital Surface Model (MDS). The computer application QGIS version 3.10 generated the Digital Elevation Model (DEM) and collected data on the trees' height and their respective canopy area through photo interpretation. The Meanshift algorithm present in the ArcGIS Pro® computer application performed the automatic segmentation of the crowns. The height and canopy data inventory comparison happened using the conventional method and image analysis. RStudio software version 4.1.0 performed the data comparison and descriptive analysis. Data were validated using linear regression analysis, and the models were compared using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results indicate that using geotechnologies and field data allowed municipal street trees' spatial and diversity characterization. Regarding the variables analyzed, the methods showed no significant difference for the Meliaceae family (p-value > 0.05) and for the species Handroanthus chrysotrichus and Melia azedarach, (pvalue > 0.05). In addition, Fabaceae and Bignoneaceae families had a higher average height than the other families. The canopy area values were higher for the conventional method (p-value < 0.05), differing from the other methods. Automatic segmentation showed no significant difference compared to photo interpretation (p-value > 0.05). The conclusion says that the use of geotechnologies helps diagnose the urban forest, enabling spatial characterization and obtaining essential quantitative variables for planning. In addition, the use of data obtained by RPAS and image processing techniques are rapidly and constantly expanding, demonstrating efficiency and potential for use in road afforestation management. |
publishDate |
2022 |
dc.date.accessioned.fl_str_mv |
2022-04-25T15:44:11Z |
dc.date.available.fl_str_mv |
2022-04-25T15:44:11Z |
dc.date.issued.fl_str_mv |
2022-03-07 |
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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masterThesis |
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dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/24178 |
url |
http://repositorio.ufsm.br/handle/1/24178 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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500200000003 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 600 600 |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Florestal |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Recursos Florestais e Engenharia Florestal |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
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