Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos

Detalhes bibliográficos
Autor(a) principal: Wrublack, Suzana Costa
Data de Publicação: 2016
Tipo de documento: Tese
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
Texto Completo: http://tede.unioeste.br:8080/tede/handle/tede/257
Resumo: This research aimed to contribute to the monitoring of water quality using orbital remote sensing and GIS techniques, use and occupation of mapping land in Lontra river watershed, focusing on information to apply water resources management instruments. The first phase consisted on mapping the use and soil occupation and on evaluating quality of irrigation water used in Salto do Lontra municipality, in Paraná state, Brazil. SPOT-5 satellite images were used to carry out the supervised classification of the Maximum Likelihood algorithm ML. Water quality data were submitted to statistical analyses by the PCA and FA techniques, in order to identify the most relevant variables during the evaluation of irrigation water quality. The UCS characterization by maximum likelihood estimation allowed identifying the classes: agricultural crops, bare soil, forest and urban area. The PCA use concerning parameters of irrigation water quality explained 53.27% of variation in water quality according to the monitored points, represented by family-based farming. In a second phase, a variation of water quality was studied along Lontra river, with the support of Geographic Information Systems (GIS) integrated with multivariate statistical techniques to investigate the dependency relationships among variables responses associated with UCS. Mosaic images of 2014 from Google Earth were used to map such land use and occupation. Digital Elevation Model (DEM) and soil maps made up database, along with UCS categories, defined as explanatory variables. The definition of areas of influence by Thiessen polygon method and multivariate statistics techniques, especially the Redundancy Analysis (RDA), were used to investigate correlation among explanatory variables (land use and occupation, slope, soil types and monitoring points) in parameters such as water quality, defined as exploratory variables. Land use mapping and Linear Redundancy Analysis allowed the identification of anthropogenic pressures on water quality parameters, especially when compared to points located by upstream and downstream of Lontras s river watershed. Finally, an approach concerning the use of Geotechnologies on the study of environmental issues was carried out focusing the contribution of information to apply water resources management instruments. The UCS characterization, using SAM supervised classification and Landsat-8 image, defined five UCS categories that with different seasons and monitoring points (upstream and downstream watershed) investigated the correlation among these variables and water quality parameters. RDA identified positive correlation among dependent variables (electrical conductivity and total dissolved solids) and warmer seasons (fall, spring and summer). The highest answers of temperature and pH were positively related to land use especially in the categories of forest, water and pasture. Temporary crops and urban areas showed negative correlation to other UCS categories. The correlation of turbidity and reducing oxidation potential parameters, especially during the winter season. Geotechnologies used in this trial, especially represented by geoprocessing and GIS, have allowed the study of geographical space structure and environmental aspects. Multivariate statistical methods enabled the synthesis of data variability structure and identification of the most significant variables, especially to the seasons and different monitoring points along the Lontra river watershed. This research mainly focused on irrigated family farming, where subsidies have been raised to assist with management decision-making on water use and the development of actions in the application of available rational technologies, aiming at improving different water use systems. Remote sensing techniques combined with GIS have contributed to carry out studies concerning management of territories and, in particular, water resources management.
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spelling Mercante, EriveltoCPF:01790206928http://lattes.cnpq.br/4061800207647478Poleto, CristianoCPF:25741607896http://lattes.cnpq.br/8672929134273036Bortoli, MarceloCPF:03796696929http://lattes.cnpq.br/6720828709289767Coelho, Silvia Renata MachadoCPF:88213943600http://lattes.cnpq.br/3554106124561773Prior, MaritaneCPF:01925843912http://lattes.cnpq.br/4825760115389832CPF:95632581934http://lattes.cnpq.br/5219250617354862Wrublack, Suzana Costa2017-05-12T14:47:33Z2016-07-202016-02-12WRUBLACK, Suzana Costa. Combined application of orbital remote sensing and geographic information system techniques on water resources management. 2016. 120 f. Tese (Doutorado em Engenharia) - Universidade Estadual do Oeste do Parana, Cascavel, 2016.http://tede.unioeste.br:8080/tede/handle/tede/257This research aimed to contribute to the monitoring of water quality using orbital remote sensing and GIS techniques, use and occupation of mapping land in Lontra river watershed, focusing on information to apply water resources management instruments. The first phase consisted on mapping the use and soil occupation and on evaluating quality of irrigation water used in Salto do Lontra municipality, in Paraná state, Brazil. SPOT-5 satellite images were used to carry out the supervised classification of the Maximum Likelihood algorithm ML. Water quality data were submitted to statistical analyses by the PCA and FA techniques, in order to identify the most relevant variables during the evaluation of irrigation water quality. The UCS characterization by maximum likelihood estimation allowed identifying the classes: agricultural crops, bare soil, forest and urban area. The PCA use concerning parameters of irrigation water quality explained 53.27% of variation in water quality according to the monitored points, represented by family-based farming. In a second phase, a variation of water quality was studied along Lontra river, with the support of Geographic Information Systems (GIS) integrated with multivariate statistical techniques to investigate the dependency relationships among variables responses associated with UCS. Mosaic images of 2014 from Google Earth were used to map such land use and occupation. Digital Elevation Model (DEM) and soil maps made up database, along with UCS categories, defined as explanatory variables. The definition of areas of influence by Thiessen polygon method and multivariate statistics techniques, especially the Redundancy Analysis (RDA), were used to investigate correlation among explanatory variables (land use and occupation, slope, soil types and monitoring points) in parameters such as water quality, defined as exploratory variables. Land use mapping and Linear Redundancy Analysis allowed the identification of anthropogenic pressures on water quality parameters, especially when compared to points located by upstream and downstream of Lontras s river watershed. Finally, an approach concerning the use of Geotechnologies on the study of environmental issues was carried out focusing the contribution of information to apply water resources management instruments. The UCS characterization, using SAM supervised classification and Landsat-8 image, defined five UCS categories that with different seasons and monitoring points (upstream and downstream watershed) investigated the correlation among these variables and water quality parameters. RDA identified positive correlation among dependent variables (electrical conductivity and total dissolved solids) and warmer seasons (fall, spring and summer). The highest answers of temperature and pH were positively related to land use especially in the categories of forest, water and pasture. Temporary crops and urban areas showed negative correlation to other UCS categories. The correlation of turbidity and reducing oxidation potential parameters, especially during the winter season. Geotechnologies used in this trial, especially represented by geoprocessing and GIS, have allowed the study of geographical space structure and environmental aspects. Multivariate statistical methods enabled the synthesis of data variability structure and identification of the most significant variables, especially to the seasons and different monitoring points along the Lontra river watershed. This research mainly focused on irrigated family farming, where subsidies have been raised to assist with management decision-making on water use and the development of actions in the application of available rational technologies, aiming at improving different water use systems. Remote sensing techniques combined with GIS have contributed to carry out studies concerning management of territories and, in particular, water resources management.Este trabalho teve por objetivo contribuir a partir de técnicas ligadas ao Sensoriamento Remoto Orbital e SIG, no monitoramento da qualidade da água, mapeamento do uso e ocupação do solo na microbacia do rio Lontra, com foco na contribuição de informações para aplicação dos instrumentos de gestão dos recursos hídricos. Em uma primeira análise, realizaram-se o mapeamento do Uso e Ocupação do Solo (UCS) e a avaliação da qualidade da água utilizada para irrigação no município de Salto do Lontra, Estado do Paraná. Imagens do satélite SPOT-5 foram utilizadas para realizar a classificação supervisionada pelo algoritmo de Máxima Verossimilhança MAXVER. Os dados de qualidade da água foram submetidos às análises estatísticas pelas técnicas de Análise de Componentes Principais (ACP) e Análise Fatorial (AF), para a identificação das variáveis mais relevantes na avaliação da qualidade da água de irrigação. A caracterização do UCS pelo classificador MAXVER permitiu a identificação das classes: culturas agrícolas, solo exposto/resteva, mata e área urbana. A aplicação da ACP dos parâmetros de qualidade da água de irrigação explicou 53,27% da variação da qualidade da água entre os pontos monitorados, representados pelas propriedades rurais de base familiar. Em um segundo momento, a variação da qualidade da água foi estudada ao longo do rio Lontra, com o apoio dos Sistemas de Informações Geográficas (SIG) integradas às técnicas estatísticas multivariadas para a averiguação das relações de dependência entre as variáveis respostas associadas ao UCS. Foram utilizadas imagens mosaicadas datadas do ano 2014, provenientes do Google Earth para o mapeamento de uso e ocupação do solo. O Modelo Digital de Elevação (MDE) e os mapas de tipos de solos serviram para compor o banco de dados, juntamente com as categorias de UCS, definidos como variáveis explicativas. A definição das áreas de influência pela técnica de polígonos de Thiessen e as técnicas estatísticas multivariadas, em especial à Análise de Redundância (RDA) foram utilizadas para investigação da correlação entre as variáveis explicativas (UCS, declividade, tipos de solos e pontos de monitoramento) nos parâmetros de qualidade da água, definidas como variáveis exploratórias. O mapeamento do UCS e a Análise de Redundância Linear RDA possibilitaram a identificação das pressões antrópicas sobre os parâmetros de qualidade da água, especialmente quando comparado aos pontos situados a montante e a jusante da microbacia do rio Lontra. Finalmente, foi conduzida uma abordagem acerca da utilização das Geotecnologias no estudo do espaço ambiental, com foco na contribuição de informações para aplicação dos instrumentos de gestão dos recursos hídricos. A caracterização do UCS, mediante a Classificação Supervisionada SAM da imagem Landsat- 8, possibilitou a definição de cinco categorias de UCS, que junto às distintas estações do ano e pontos de monitoramento (a montante e a jusante da microbacia) buscaram investigar a correlação destas variáveis com os parâmetros de qualidade da água. Pela RDA, identificou-se a correlação positiva para as variáveis dependentes (condutividade elétrica e sólidos totais dissolvidos) relacionadas com as estações mais quentes (outono, primavera e verão). Valores mais elevados de temperatura e pH estiveram positivamente relacionados aos usos do solo especialmente nas categorias de mata, água e pastagens. As culturas temporárias e área urbana demonstraram estar negativamente correlacionadas às demais categorias de UCS. A correlação dos parâmetros de turbidez e potencial redutor de oxidação, principalmente na estação do inverno. As geotecnologias utilizadas neste trabalho, especialmente representadas pelas técnicas de geoprocessamento e dos SIG s, possibilitaram o estudo da estrutura do espaço geográfico e dos aspectos ambientais. Os métodos estatísticos multivariados possibilitaram a sintetização da estrutura de variabilidade dos dados e a identificação das variáveis mais significativas, com destaque às estações do ano e aos distintos pontos de monitoramento ao longo da microbacia do rio Lontra. A viii aplicação conjunta de técnicas de sensoriamento remoto orbital e SIG contribuiu para condução de estudos voltados a gestão dos territórios e em especial à gestão dos recursos hídricos. A pesquisa teve como foco principal a agricultura familiar irrigada, em que foram levantados subsídios que pudessem auxiliar nas decisões gerenciais sobre o uso da água e no desenvolvimento de ações para a aplicação de tecnologias racionais disponíveis, visando à melhoriaMade available in DSpace on 2017-05-12T14:47:33Z (GMT). No. of bitstreams: 1 Suzana_ Costa Wrublack.pdf: 1543674 bytes, checksum: a147c806a7c505117131dbc0077215e4 (MD5) Previous issue date: 2016-02-12application/pdfporUniversidade Estadual do Oeste do ParanaPrograma de Pós-Graduação "Stricto Sensu" em Engenharia AgrícolaUNIOESTEBREngenhariaEspaço geográficoInformações georreferenciadasUso sustentável do soloGeographic areaManagement georeferencedSustainable land useCNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLAAplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricosCombined application of orbital remote sensing and geographic information system techniques on water resources managementinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações do UNIOESTEinstname:Universidade Estadual do Oeste do Paraná (UNIOESTE)instacron:UNIOESTEORIGINALSuzana_ Costa Wrublack.pdfapplication/pdf1543674http://tede.unioeste.br:8080/tede/bitstream/tede/257/1/Suzana_+Costa+Wrublack.pdfa147c806a7c505117131dbc0077215e4MD51tede/2572017-05-12 11:47:33.141oai:tede.unioeste.br:tede/257Biblioteca Digital de Teses e Dissertaçõeshttp://tede.unioeste.br/PUBhttp://tede.unioeste.br/oai/requestbiblioteca.repositorio@unioeste.bropendoar:2017-05-12T14:47:33Biblioteca Digital de Teses e Dissertações do UNIOESTE - Universidade Estadual do Oeste do Paraná (UNIOESTE)false
dc.title.por.fl_str_mv Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
dc.title.alternative.eng.fl_str_mv Combined application of orbital remote sensing and geographic information system techniques on water resources management
title Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
spellingShingle Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
Wrublack, Suzana Costa
Espaço geográfico
Informações georreferenciadas
Uso sustentável do solo
Geographic area
Management georeferenced
Sustainable land use
CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
title_short Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
title_full Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
title_fullStr Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
title_full_unstemmed Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
title_sort Aplicação conjunta das técnicas de sensoriamento remoto orbital e sistemas de informações geográficas na gestão dos recursos hídricos
author Wrublack, Suzana Costa
author_facet Wrublack, Suzana Costa
author_role author
dc.contributor.advisor1.fl_str_mv Mercante, Erivelto
dc.contributor.advisor1ID.fl_str_mv CPF:01790206928
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/4061800207647478
dc.contributor.referee1.fl_str_mv Poleto, Cristiano
dc.contributor.referee1ID.fl_str_mv CPF:25741607896
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/8672929134273036
dc.contributor.referee2.fl_str_mv Bortoli, Marcelo
dc.contributor.referee2ID.fl_str_mv CPF:03796696929
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/6720828709289767
dc.contributor.referee3.fl_str_mv Coelho, Silvia Renata Machado
dc.contributor.referee3ID.fl_str_mv CPF:88213943600
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/3554106124561773
dc.contributor.referee4.fl_str_mv Prior, Maritane
dc.contributor.referee4ID.fl_str_mv CPF:01925843912
dc.contributor.referee4Lattes.fl_str_mv http://lattes.cnpq.br/4825760115389832
dc.contributor.authorID.fl_str_mv CPF:95632581934
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/5219250617354862
dc.contributor.author.fl_str_mv Wrublack, Suzana Costa
contributor_str_mv Mercante, Erivelto
Poleto, Cristiano
Bortoli, Marcelo
Coelho, Silvia Renata Machado
Prior, Maritane
dc.subject.por.fl_str_mv Espaço geográfico
Informações georreferenciadas
Uso sustentável do solo
topic Espaço geográfico
Informações georreferenciadas
Uso sustentável do solo
Geographic area
Management georeferenced
Sustainable land use
CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
dc.subject.eng.fl_str_mv Geographic area
Management georeferenced
Sustainable land use
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
description This research aimed to contribute to the monitoring of water quality using orbital remote sensing and GIS techniques, use and occupation of mapping land in Lontra river watershed, focusing on information to apply water resources management instruments. The first phase consisted on mapping the use and soil occupation and on evaluating quality of irrigation water used in Salto do Lontra municipality, in Paraná state, Brazil. SPOT-5 satellite images were used to carry out the supervised classification of the Maximum Likelihood algorithm ML. Water quality data were submitted to statistical analyses by the PCA and FA techniques, in order to identify the most relevant variables during the evaluation of irrigation water quality. The UCS characterization by maximum likelihood estimation allowed identifying the classes: agricultural crops, bare soil, forest and urban area. The PCA use concerning parameters of irrigation water quality explained 53.27% of variation in water quality according to the monitored points, represented by family-based farming. In a second phase, a variation of water quality was studied along Lontra river, with the support of Geographic Information Systems (GIS) integrated with multivariate statistical techniques to investigate the dependency relationships among variables responses associated with UCS. Mosaic images of 2014 from Google Earth were used to map such land use and occupation. Digital Elevation Model (DEM) and soil maps made up database, along with UCS categories, defined as explanatory variables. The definition of areas of influence by Thiessen polygon method and multivariate statistics techniques, especially the Redundancy Analysis (RDA), were used to investigate correlation among explanatory variables (land use and occupation, slope, soil types and monitoring points) in parameters such as water quality, defined as exploratory variables. Land use mapping and Linear Redundancy Analysis allowed the identification of anthropogenic pressures on water quality parameters, especially when compared to points located by upstream and downstream of Lontras s river watershed. Finally, an approach concerning the use of Geotechnologies on the study of environmental issues was carried out focusing the contribution of information to apply water resources management instruments. The UCS characterization, using SAM supervised classification and Landsat-8 image, defined five UCS categories that with different seasons and monitoring points (upstream and downstream watershed) investigated the correlation among these variables and water quality parameters. RDA identified positive correlation among dependent variables (electrical conductivity and total dissolved solids) and warmer seasons (fall, spring and summer). The highest answers of temperature and pH were positively related to land use especially in the categories of forest, water and pasture. Temporary crops and urban areas showed negative correlation to other UCS categories. The correlation of turbidity and reducing oxidation potential parameters, especially during the winter season. Geotechnologies used in this trial, especially represented by geoprocessing and GIS, have allowed the study of geographical space structure and environmental aspects. Multivariate statistical methods enabled the synthesis of data variability structure and identification of the most significant variables, especially to the seasons and different monitoring points along the Lontra river watershed. This research mainly focused on irrigated family farming, where subsidies have been raised to assist with management decision-making on water use and the development of actions in the application of available rational technologies, aiming at improving different water use systems. Remote sensing techniques combined with GIS have contributed to carry out studies concerning management of territories and, in particular, water resources management.
publishDate 2016
dc.date.available.fl_str_mv 2016-07-20
dc.date.issued.fl_str_mv 2016-02-12
dc.date.accessioned.fl_str_mv 2017-05-12T14:47:33Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv WRUBLACK, Suzana Costa. Combined application of orbital remote sensing and geographic information system techniques on water resources management. 2016. 120 f. Tese (Doutorado em Engenharia) - Universidade Estadual do Oeste do Parana, Cascavel, 2016.
dc.identifier.uri.fl_str_mv http://tede.unioeste.br:8080/tede/handle/tede/257
identifier_str_mv WRUBLACK, Suzana Costa. Combined application of orbital remote sensing and geographic information system techniques on water resources management. 2016. 120 f. Tese (Doutorado em Engenharia) - Universidade Estadual do Oeste do Parana, Cascavel, 2016.
url http://tede.unioeste.br:8080/tede/handle/tede/257
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