Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional Manancial UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/30273 |
Resumo: | The mapping of floodable areas is a non-structural measure, which acts as a control measure, assisting the decision-making process of State entities, which have the legislative obligation to carry out urban planning aimed at preventing disasters and calamities, such as floods. This study aimed to analyze the uncertainties of a flood mapping made from remote sensing, using satellite images (ALOS and SRTM), compared to the mapping of a flood event, in a sub-basin located within the basin hydrographic analysis of the Piabanha River, made with field topography data. The two digital elevation models (DEM) were filtered in the CloudCompare software, generating two new DEMs for analysis. The DEMs were subjected to the modeling process in the HE CRAS software, following the same parameters used in the original reference modeling. The results showed that the mapping of flood areas, made using remote sensing, can be applied in places where there is no mapping of the flood area, in an accessible way and can be carried out from any location. The modeling must be done with the filtered DEMs, which obtained higher levels of combination with the reference mapping and that a margin of error is added around the modeling, especially in stretches where the watercourse has sinuous curves, since the Modeling does not precisely delimit these areas. The data shows that approximately 40% of the modeling done by remote sensing would occupy a zone with a high probability of flooding and the remainder can be delimited as a medium and low probability zone, at the planner's discretion. Finally, the objective of the study was concluded, identifying the uncertainties of flood mapping with remote sensing and suggesting points of attention for the application of the method in other analyses. In this way, one of the main urban problems in Brazilian municipalities, floods, can have a source of supporting data, so that prevention measures can be taken, without the need for excessive professional and financial resources. Furthermore, researchers and universities can remotely map the basins and make them publicly available, so that the committees responsible for the river basins or public administrators can use them during the management of municipalities, helping urban planning that prevents the impacts of the flooding process. |
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2023-09-26T11:33:04Z2023-09-26T11:33:04Z2023-07-21http://repositorio.ufsm.br/handle/1/30273The mapping of floodable areas is a non-structural measure, which acts as a control measure, assisting the decision-making process of State entities, which have the legislative obligation to carry out urban planning aimed at preventing disasters and calamities, such as floods. This study aimed to analyze the uncertainties of a flood mapping made from remote sensing, using satellite images (ALOS and SRTM), compared to the mapping of a flood event, in a sub-basin located within the basin hydrographic analysis of the Piabanha River, made with field topography data. The two digital elevation models (DEM) were filtered in the CloudCompare software, generating two new DEMs for analysis. The DEMs were subjected to the modeling process in the HE CRAS software, following the same parameters used in the original reference modeling. The results showed that the mapping of flood areas, made using remote sensing, can be applied in places where there is no mapping of the flood area, in an accessible way and can be carried out from any location. The modeling must be done with the filtered DEMs, which obtained higher levels of combination with the reference mapping and that a margin of error is added around the modeling, especially in stretches where the watercourse has sinuous curves, since the Modeling does not precisely delimit these areas. The data shows that approximately 40% of the modeling done by remote sensing would occupy a zone with a high probability of flooding and the remainder can be delimited as a medium and low probability zone, at the planner's discretion. Finally, the objective of the study was concluded, identifying the uncertainties of flood mapping with remote sensing and suggesting points of attention for the application of the method in other analyses. In this way, one of the main urban problems in Brazilian municipalities, floods, can have a source of supporting data, so that prevention measures can be taken, without the need for excessive professional and financial resources. Furthermore, researchers and universities can remotely map the basins and make them publicly available, so that the committees responsible for the river basins or public administrators can use them during the management of municipalities, helping urban planning that prevents the impacts of the flooding process.O mapeamento de áreas inundáveis é uma medida não-estrutural, que atua como uma medida de controle, auxiliando o processo de tomada de decisão dos entes do Estado, que tem a obrigação legislativa de efetuarem planejamentos urbanos visando à prevenção de desastres e calamidades, como as inundações. Esse estudo teve por objetivo analisar as incertezas de um mapeamento de inundação feito a partir de sensoriamento remoto, com a utilização de imagens de satélite (ALOS e SRTM), comparando ao mapeamento de um evento de cheia, numa sub-bacia localizada dentro da bacia hidrográfica do rio Piabanha, feito com dados de topografia a campo. Os dois modelos digitais de elevação (MDE) foram submetidos a uma filtragem no software CloudCompare, gerando dois novos MDEs para a análise. Os MDEs foram submetidos ao processo de modelagem no software HECRAS, seguindo os mesmos parâmetros utilizados na modelagem original de referência. Os resultados mostraram que o mapeamento das áreas de inundação, feito a partir de sensoriamento remoto, é possível de ser aplicado em locais onde não há um mapeamento da área de inundação, de modo acessível e podendo ser realizado de qualquer localidade. A modelagem deve ser feita com os MDEs filtrados, que obtiveram maiores índices de combinação com o mapeamento de referência e que seja acrescentada uma margem de erro no entorno da modelagem, principalmente em trechos onde o curso d’água possui curvas sinuosas, visto que a modelagem não delimita com precisão essas áreas. Os dados mostram que aproximadamente 40% da modelagem feita por sensoriamento remoto ocupariam uma zona com alta probabilidade de inundação e o restante pode ser delimitado como zona de média e baixa probabilidade, a critério do planejador. Por fim, o objetivo do estudo foi concluído, identificando as incertezas do mapeamento de inundação com sensoriamento remoto e sugerindo pontos de atenção para a aplicação do método em outras análises. Dessa forma, um dos principais problemas urbanos dos municípios brasileiros, as inundações, podem ter uma fonte dados de embasamento, para que medidas de prevenção sejam tomadas, sem o desprendimento de excessivos recursos profissionais e financeiros. Outrossim, pesquisadores e universidades, podem mapear remotamente as bacias e disponibilizar publicamente, para que os comitês responsáveis pelas bacias hidrográficas ou administradores públicos, possam utilizar durante a gestão dos municípios, auxiliando um planejamento urbano que previna os impactos do processo de inundação.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Engenharia AmbientalUFSMBrasilEngenharia AmbientalAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessInundaçãoSensoriamento remotoPlanejamento urbanoMapeamento de áreas inundáveisInundationRemote sensingUrban planningMapping of floodable areasCNPQ::ENGENHARIASMapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezasMapping of flood areas using remote sensing: uncertainty analysisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisCruz, Rafael Cabralhttp://lattes.cnpq.br/1246969166762146Piccili, Daniel AlasiaTrentin, Aline Biasolihttp://lattes.cnpq.br/0153754005033310Abib, Viviane Caroline Oliveira3000000000096006006006006007a3ccff3-7a95-4508-a926-f64c7c17202ec1bbfa6e-b92d-4088-a341-b76642d01eec709b8be4-6de6-4b8a-ae29-4a85ed2417c6c8e9d60d-e59e-4dae-b0ff-6a00b7d8337dreponame:Repositório Institucional Manancial UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGEA_2023_ABIB_VIVIANE.pdfDIS_PPGEA_2023_ABIB_VIVIANE.pdfDissertaçãoapplication/pdf3277932http://repositorio.ufsm.br/bitstream/1/30273/1/DIS_PPGEA_2023_ABIB_VIVIANE.pdf8f900b591ea2f2bab5d387c04edd4917MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/30273/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/30273/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD531/302732023-09-26 08:33:04.809oai:repositorio.ufsm.br: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ório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestouvidoria@ufsm.bropendoar:39132023-09-26T11:33:04Repositório Institucional Manancial UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
dc.title.alternative.eng.fl_str_mv |
Mapping of flood areas using remote sensing: uncertainty analysis |
title |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
spellingShingle |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas Abib, Viviane Caroline Oliveira Inundação Sensoriamento remoto Planejamento urbano Mapeamento de áreas inundáveis Inundation Remote sensing Urban planning Mapping of floodable areas CNPQ::ENGENHARIAS |
title_short |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
title_full |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
title_fullStr |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
title_full_unstemmed |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
title_sort |
Mapeamento de áreas inundáveis através de sensoriamento remoto: análise de incertezas |
author |
Abib, Viviane Caroline Oliveira |
author_facet |
Abib, Viviane Caroline Oliveira |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Cruz, Rafael Cabral |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/1246969166762146 |
dc.contributor.referee1.fl_str_mv |
Piccili, Daniel Alasia |
dc.contributor.referee2.fl_str_mv |
Trentin, Aline Biasoli |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0153754005033310 |
dc.contributor.author.fl_str_mv |
Abib, Viviane Caroline Oliveira |
contributor_str_mv |
Cruz, Rafael Cabral Piccili, Daniel Alasia Trentin, Aline Biasoli |
dc.subject.por.fl_str_mv |
Inundação Sensoriamento remoto Planejamento urbano Mapeamento de áreas inundáveis |
topic |
Inundação Sensoriamento remoto Planejamento urbano Mapeamento de áreas inundáveis Inundation Remote sensing Urban planning Mapping of floodable areas CNPQ::ENGENHARIAS |
dc.subject.eng.fl_str_mv |
Inundation Remote sensing Urban planning Mapping of floodable areas |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS |
description |
The mapping of floodable areas is a non-structural measure, which acts as a control measure, assisting the decision-making process of State entities, which have the legislative obligation to carry out urban planning aimed at preventing disasters and calamities, such as floods. This study aimed to analyze the uncertainties of a flood mapping made from remote sensing, using satellite images (ALOS and SRTM), compared to the mapping of a flood event, in a sub-basin located within the basin hydrographic analysis of the Piabanha River, made with field topography data. The two digital elevation models (DEM) were filtered in the CloudCompare software, generating two new DEMs for analysis. The DEMs were subjected to the modeling process in the HE CRAS software, following the same parameters used in the original reference modeling. The results showed that the mapping of flood areas, made using remote sensing, can be applied in places where there is no mapping of the flood area, in an accessible way and can be carried out from any location. The modeling must be done with the filtered DEMs, which obtained higher levels of combination with the reference mapping and that a margin of error is added around the modeling, especially in stretches where the watercourse has sinuous curves, since the Modeling does not precisely delimit these areas. The data shows that approximately 40% of the modeling done by remote sensing would occupy a zone with a high probability of flooding and the remainder can be delimited as a medium and low probability zone, at the planner's discretion. Finally, the objective of the study was concluded, identifying the uncertainties of flood mapping with remote sensing and suggesting points of attention for the application of the method in other analyses. In this way, one of the main urban problems in Brazilian municipalities, floods, can have a source of supporting data, so that prevention measures can be taken, without the need for excessive professional and financial resources. Furthermore, researchers and universities can remotely map the basins and make them publicly available, so that the committees responsible for the river basins or public administrators can use them during the management of municipalities, helping urban planning that prevents the impacts of the flooding process. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-09-26T11:33:04Z |
dc.date.available.fl_str_mv |
2023-09-26T11:33:04Z |
dc.date.issued.fl_str_mv |
2023-07-21 |
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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http://repositorio.ufsm.br/handle/1/30273 |
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http://repositorio.ufsm.br/handle/1/30273 |
dc.language.iso.fl_str_mv |
por |
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por |
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300000000009 |
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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 Tecnologia |
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Programa de Pós-Graduação em Engenharia Ambiental |
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UFSM |
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Brasil |
dc.publisher.department.fl_str_mv |
Engenharia Ambiental |
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Universidade Federal de Santa Maria Centro de Tecnologia |
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