Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja

Detalhes bibliográficos
Autor(a) principal: Damian, Júnior Melo
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Manancial - Repositório Digital da UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/11313
Resumo: The no-tillage system (SPD) was one of the main innovations in Brazilian agriculture, but there are still discussions about how to achieve and maintain its quality and sustainability. The management of SPD areas through management zones presents great potential for this purpose, since it integrates different variables in order to facilitate and increase the technical and computerized management of agricultural practices and consequently the reduction of polluting potencies in environments. Among the main variables used to delimit management zones are the chemical attributes, yield maps and recently the NDVI index. In this sense, with Article I, the objective was to delimit management zones through yield maps and NDVIs derived from satellite images in historical series. To do this, in an area of 118 ha, three yield maps of different cultures between the years of 2010 to 2015 were selected and for each yield map we searched for the images from the Landsat 5 and 8 satellite that included a date in of the cycle of the crop in question from which the NDVI was calculated and also with the intention of verifying the stability of the NDVI generated in different crop cycles, four other satellite images were selected for four crops according to the historical of the study area, between the years 2007 and 2013. In article II, the objective was to verify the variability caused by the winter cover crop in the summer crop and if the NDVI index performed by land and with a RPAS is able to evidence this variability in the summer crop. In an area 73.96 there was applied a sampling grid of 70.71 x 70.71 m (0.5 ha), where soil sampling for chemical analysis and dry matter nutrients accumulated in the winter cover crop of black oats where soybean was sown in the summer, in which in the R5 and R5.5 stages evaluations were carried out with a portable sensor "by land" and with a RPAS for obtaining of the NDVI index and finally the grain yield of the soybean was determined, as well as the final population of plants. With the results, NDVI from satellite images can replace and/or compose the yield maps (article I) and that the dry mass and accumulated nutrients in the winter crop interfere with the yield of the summer crop and the NDVI index performed by land or with a RPAS was effective in expressing this variability (article II).
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spelling 2017-08-07T15:20:46Z2017-08-07T15:20:46Z2017-01-18http://repositorio.ufsm.br/handle/1/11313The no-tillage system (SPD) was one of the main innovations in Brazilian agriculture, but there are still discussions about how to achieve and maintain its quality and sustainability. The management of SPD areas through management zones presents great potential for this purpose, since it integrates different variables in order to facilitate and increase the technical and computerized management of agricultural practices and consequently the reduction of polluting potencies in environments. Among the main variables used to delimit management zones are the chemical attributes, yield maps and recently the NDVI index. In this sense, with Article I, the objective was to delimit management zones through yield maps and NDVIs derived from satellite images in historical series. To do this, in an area of 118 ha, three yield maps of different cultures between the years of 2010 to 2015 were selected and for each yield map we searched for the images from the Landsat 5 and 8 satellite that included a date in of the cycle of the crop in question from which the NDVI was calculated and also with the intention of verifying the stability of the NDVI generated in different crop cycles, four other satellite images were selected for four crops according to the historical of the study area, between the years 2007 and 2013. In article II, the objective was to verify the variability caused by the winter cover crop in the summer crop and if the NDVI index performed by land and with a RPAS is able to evidence this variability in the summer crop. In an area 73.96 there was applied a sampling grid of 70.71 x 70.71 m (0.5 ha), where soil sampling for chemical analysis and dry matter nutrients accumulated in the winter cover crop of black oats where soybean was sown in the summer, in which in the R5 and R5.5 stages evaluations were carried out with a portable sensor "by land" and with a RPAS for obtaining of the NDVI index and finally the grain yield of the soybean was determined, as well as the final population of plants. With the results, NDVI from satellite images can replace and/or compose the yield maps (article I) and that the dry mass and accumulated nutrients in the winter crop interfere with the yield of the summer crop and the NDVI index performed by land or with a RPAS was effective in expressing this variability (article II).O Sistema Plantio Direto (SPD) foi uma das principais inovações na agricultura brasileira, contudo ainda há discussões sobre como alcançar e manter sua qualidade e sustentabilidade. A gestão de áreas sob SPD por meio de zonas de manejo, apresenta grande potencial para essa finalidade, pois integra diferentes variáveis afim de facilitar e incrementar a gestão tecnificada e informatizada das práticas agrícolas, e em consequência a redução de potencias poluidores no ambiente. Entre as principais variáveis utilizadas para delimitar zonas de manejo estão os atributos químicos, mapas de rendimento e recentemente o índice NDVI. Nesse sentido, com o artigo I objetivou-se delimitar zonas de manejo por meio de mapas de rendimento e NDVI oriundos de imagens de satélite em series históricas. Para isso, em uma área de 118 ha, selecionou-se três mapas de rendimento de diferentes culturas compreendidas entre os anos de 2010 a 2015 e para cada mapa de rendimento buscou-se selecionar as imagens satélite oriundas série Landsat que compreendessem uma data dentro do ciclo da cultura em questão a partir das quais procedeu-se o cálculo do NDVI e ainda com o intuito de verificar a estabilidade do NDVI gerado em diferentes ciclos de cultivo, foram selecionadas outras quatro imagens de satélites referentes a quatro cultivos, segundo o histórico de cultivo da área de estudo, compreendidos entre os anos de 2007 a 2013. Já no artigo II, o objetivo foi verificar a variabilidade causada pela cultura de cobertura de inverno na cultura de verão e se o índice de NDVI realizado “por terra” e com um RPAS é capaz de evidenciar essa variabilidade na cultura de verão. Em uma área 73,96 ha, aplicou-se uma malha amostral de 70,71 x 70,71 m (0,5 ha), onde realizou-se a amostragem de solo para a análise química e as avaliações de matéria seca e os nutrientes acumulados na cultura de cobertura inverno da aveia preta onde sobre esta, foi semeada no verão a cultura da soja, na qual nos estágios R5 e R5.5 foram realizadas avaliações com um sensor portátil “por terra” e com um RPAS para a obtenção do índice de NDVI e por final determinou-se o rendimento de grãos da soja, bem como, a população final de plantas. Com os resultados, constatou-se que O NDVI foi um bom parâmetro para delimitar duas zonas de manejo de alto e baixo potencial (artigo I) e que a matéria seca e os nutrientes acumulados na cultura de inverno interferem o rendimento da cultura de verão, sendo que o índice de NDVI realizado “por terra” ou com um RPAS foi eficaz em expressar essa variabilidade (artigo II).Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaUFSM Frederico WestphalenPrograma de Pós-Graduação em Agronomia - Agricultura e AmbienteUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAgricultura de precisãoCulturas de coberturaRendimento de grãosImagens de satéliteGreenSeekerSistemas de aeronaves remotamente pilotadasPrecision agricultureCover cropsGrain yieldSatellite imagesGreenSeekerRemotely piloted aircraft systemsCNPQ::CIENCIAS AGRARIAS::AGRONOMIAÍndice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/sojaNormalized differential vegetation index (NDVI) for the definition of management zone and monitoring of variability of succession black oats / soybeaninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisSanti, Antônio Luishttp://lattes.cnpq.br/6223011493102530Bredemeier, Christianhttp://lattes.cnpq.br/0364795290228832Breunig, Fabio Marcelohttp://lattes.cnpq.br/5926113161758766http://lattes.cnpq.br/1280764013770824Damian, Júnior Melo50010000000960060060060026e69663-7809-4435-8e7a-419ac889c5f32f5e0996-4e7b-494b-9c29-7809cac4b442e52de4a9-eedb-4207-9793-d43dab5b6cbcb1c4e881-5217-4dfd-848e-6ff5b3b80f48reponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDamian, Júnior Melo.pdfDamian, Júnior Melo.pdfDissertação de Mestradoapplication/pdf3216044http://repositorio.ufsm.br/bitstream/1/11313/1/Damian%2c%20J%c3%banior%20Melo.pdfe8033e93b4b194b75ce49f5f9afff47dMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.por.fl_str_mv Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
dc.title.alternative.eng.fl_str_mv Normalized differential vegetation index (NDVI) for the definition of management zone and monitoring of variability of succession black oats / soybean
title Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
spellingShingle Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
Damian, Júnior Melo
Agricultura de precisão
Culturas de cobertura
Rendimento de grãos
Imagens de satélite
GreenSeeker
Sistemas de aeronaves remotamente pilotadas
Precision agriculture
Cover crops
Grain yield
Satellite images
GreenSeeker
Remotely piloted aircraft systems
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
title_short Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
title_full Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
title_fullStr Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
title_full_unstemmed Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
title_sort Índice de vegetação por diferença normalizada (NDVI) para definição de zonas de manejo e monitoramento da variabilidade da sucessão aveia preta/soja
author Damian, Júnior Melo
author_facet Damian, Júnior Melo
author_role author
dc.contributor.advisor1.fl_str_mv Santi, Antônio Luis
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/6223011493102530
dc.contributor.referee1.fl_str_mv Bredemeier, Christian
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/0364795290228832
dc.contributor.referee2.fl_str_mv Breunig, Fabio Marcelo
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/5926113161758766
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/1280764013770824
dc.contributor.author.fl_str_mv Damian, Júnior Melo
contributor_str_mv Santi, Antônio Luis
Bredemeier, Christian
Breunig, Fabio Marcelo
dc.subject.por.fl_str_mv Agricultura de precisão
Culturas de cobertura
Rendimento de grãos
Imagens de satélite
GreenSeeker
Sistemas de aeronaves remotamente pilotadas
topic Agricultura de precisão
Culturas de cobertura
Rendimento de grãos
Imagens de satélite
GreenSeeker
Sistemas de aeronaves remotamente pilotadas
Precision agriculture
Cover crops
Grain yield
Satellite images
GreenSeeker
Remotely piloted aircraft systems
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
dc.subject.eng.fl_str_mv Precision agriculture
Cover crops
Grain yield
Satellite images
GreenSeeker
Remotely piloted aircraft systems
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
description The no-tillage system (SPD) was one of the main innovations in Brazilian agriculture, but there are still discussions about how to achieve and maintain its quality and sustainability. The management of SPD areas through management zones presents great potential for this purpose, since it integrates different variables in order to facilitate and increase the technical and computerized management of agricultural practices and consequently the reduction of polluting potencies in environments. Among the main variables used to delimit management zones are the chemical attributes, yield maps and recently the NDVI index. In this sense, with Article I, the objective was to delimit management zones through yield maps and NDVIs derived from satellite images in historical series. To do this, in an area of 118 ha, three yield maps of different cultures between the years of 2010 to 2015 were selected and for each yield map we searched for the images from the Landsat 5 and 8 satellite that included a date in of the cycle of the crop in question from which the NDVI was calculated and also with the intention of verifying the stability of the NDVI generated in different crop cycles, four other satellite images were selected for four crops according to the historical of the study area, between the years 2007 and 2013. In article II, the objective was to verify the variability caused by the winter cover crop in the summer crop and if the NDVI index performed by land and with a RPAS is able to evidence this variability in the summer crop. In an area 73.96 there was applied a sampling grid of 70.71 x 70.71 m (0.5 ha), where soil sampling for chemical analysis and dry matter nutrients accumulated in the winter cover crop of black oats where soybean was sown in the summer, in which in the R5 and R5.5 stages evaluations were carried out with a portable sensor "by land" and with a RPAS for obtaining of the NDVI index and finally the grain yield of the soybean was determined, as well as the final population of plants. With the results, NDVI from satellite images can replace and/or compose the yield maps (article I) and that the dry mass and accumulated nutrients in the winter crop interfere with the yield of the summer crop and the NDVI index performed by land or with a RPAS was effective in expressing this variability (article II).
publishDate 2017
dc.date.accessioned.fl_str_mv 2017-08-07T15:20:46Z
dc.date.available.fl_str_mv 2017-08-07T15:20:46Z
dc.date.issued.fl_str_mv 2017-01-18
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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
UFSM Frederico Westphalen
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Agronomia - Agricultura e Ambiente
dc.publisher.initials.fl_str_mv UFSM
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Agronomia
publisher.none.fl_str_mv Universidade Federal de Santa Maria
UFSM Frederico Westphalen
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