Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)

É de extrema relevância entender o comportamento da vegetação para o planejamento e tomada de decisão no que se refere as áreas para plantio, uso adequado de recursos hídricos, irrigação e acompanhamento de dinâmicas vegetacionais, por exemplo. Neste sentido, o Sensoriamento Remoto (SR) vem sendo um...

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Published in:Journal of Hyperspectral Remote Sensing
Main Authors: Freire-Silva, Jadson, Paz, Yenê Medeiros, Lima-Silva, Pedro Paulo, Pereira, João Antonio dos Santos, Candeias, Ana Lúcia Bezerra
Other Authors: FACEPE - Fundação de Amparo à Ciência e Tecnologia de Pernambuco
Format: Article in Journal/Newspaper
Language:Portuguese
Published: UFPE 2019
Subjects:
Alta
Arctic
Online Access:https://periodicos.ufpe.br/revistas/jhrs/article/view/242924
https://doi.org/10.29150/jhrs.v9.4.p228-239
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description É de extrema relevância entender o comportamento da vegetação para o planejamento e tomada de decisão no que se refere as áreas para plantio, uso adequado de recursos hídricos, irrigação e acompanhamento de dinâmicas vegetacionais, por exemplo. Neste sentido, o Sensoriamento Remoto (SR) vem sendo um relevante suporte para o monitoramento de ecossistemas, uma vez que se observa diversas pesquisas envolvendo a aplicação desta técnica através de diferentes algoritmos matemáticos intitulados índices. Os novos satélites, os veículos não tripulados e as câmeras de alta resolução que mantém produtos na faixa do visível (RGB) trazem novas perspectivas para a atuação do SR na vegetação, sobretudo na agricultura; assim, foi desenvolvido ao longo dos anos índices que possibilitasse a detecção da vegetação nas faixas espectrais visíveis e dessa forma, facilitando processos agropastoris, de agricultura de precisão e no barateamento do SR como um todo. Deste modo, este trabalho tem como objetivo uma revisão acerca dos índices de vegetação para o processamento na faixa RGB. A partir da revisão, verifica-se a procedência de quinze índices RGB, sendo concebidos por necessidades e equipamentos diversos, onde todos alcançam satisfatoriedade competida. Contata-se que os índices desenvolvidos melhoraram em significância as análises do SR, e que essas melhorias acarretaram novos aprendizados que contribuíram diretamente para o estudo dos ecossistemas, especialmente os ambientes vegetacionais. O dinamismo do SR o faz chamariz de inovação, em que, através das exigências e de demandas atuais, novos índices poderão ser criados contribuindo na manutenção e provimento de atividades sociais, econômicas e ecológicas.
author2 FACEPE - Fundação de Amparo à Ciência e Tecnologia de Pernambuco
format Article in Journal/Newspaper
author Freire-Silva, Jadson
Paz, Yenê Medeiros
Lima-Silva, Pedro Paulo
Pereira, João Antonio dos Santos
Candeias, Ana Lúcia Bezerra
spellingShingle Freire-Silva, Jadson
Paz, Yenê Medeiros
Lima-Silva, Pedro Paulo
Pereira, João Antonio dos Santos
Candeias, Ana Lúcia Bezerra
Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)
author_facet Freire-Silva, Jadson
Paz, Yenê Medeiros
Lima-Silva, Pedro Paulo
Pereira, João Antonio dos Santos
Candeias, Ana Lúcia Bezerra
author_sort Freire-Silva, Jadson
title Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)
title_short Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)
title_full Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)
title_fullStr Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)
title_full_unstemmed Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)
title_sort índices de vegetação do sensoriamento remoto para processamento de imagens na faixa do visível (rgb)
publisher UFPE
publishDate 2019
url https://periodicos.ufpe.br/revistas/jhrs/article/view/242924
https://doi.org/10.29150/jhrs.v9.4.p228-239
geographic Alta
geographic_facet Alta
genre Arctic
genre_facet Arctic
op_source Journal of Hyperspectral Remote Sensing; v. 9, n. 4 (2019): Journal of Hyperspectral Remote Sensing; 228-239
2237-2202
op_relation https://periodicos.ufpe.br/revistas/jhrs/article/view/242924/34089
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spelling ftunifpernambojs:oai:oai.periodicos.ufpe.br:article/242924 2023-06-11T04:07:52+02:00 Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB) Freire-Silva, Jadson Paz, Yenê Medeiros Lima-Silva, Pedro Paulo Pereira, João Antonio dos Santos Candeias, Ana Lúcia Bezerra FACEPE - Fundação de Amparo à Ciência e Tecnologia de Pernambuco 2019-12-26 application/pdf https://periodicos.ufpe.br/revistas/jhrs/article/view/242924 https://doi.org/10.29150/jhrs.v9.4.p228-239 por por UFPE https://periodicos.ufpe.br/revistas/jhrs/article/view/242924/34089 Alexakis, D.D.; Grillakis, M.G.; Koutroulis, A.G.; Agapiou, A.; Themistocleous, K.; Tsanis, I.K.; Michaelides, S.; Pashiardis, S.; Demetriou, C.; Aristeidou, K.; Retalis, A.; Tymvios, F.; Hadjimitsis, D.G. GIS and remote sensing techniques for the assessment of land use change impact on flood hydrology: the case study of Yialias basin in Cyprus.Nat. Hazards Earth Syst. Sci., v. 14, p. 413–426, 2014. Alves, D.S.; Skole, D.L. Characterizing land cover dynamics using multi-temporal imagery. Int. Remote Sensing, v. 17, n. 4, p. 835-839, 1996. Atzberger, C. Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs. Remote Sens, v. 5, 949-981, 2013. Barbosa, R.V.R.; Vecchia, F.A.S. Estudos de ilha de calor urbana por meio de imagens do Landsat 7 ETM+: Estudo de caso em São Carlos (SP). Revista Minerva, v. 6, n. 3, p. 273-278, 2009. Batten, G.D. Plant analysis using near infrared reflectance spectroscopy: The potential and the limitations. Australian Journal of Experimental Agriculture, v. 38, n.7, p. 697–706, 1997. Bastiaanssen, W. Remote sensing in water resources management: the state of the art. IX ed. Colombo, Sri Lanka: International Water Management Institute (IWMI), 1998. Bastiaanssen, W.G.M.; Molden, D.J.; Makin, I.W. 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International Journal of Remote Sensing, v. 24, p. 583–594, 2003. https://periodicos.ufpe.br/revistas/jhrs/article/view/242924 doi:10.29150/jhrs.v9.4.p228-239 Direitos autorais 2019 Journal of Hyperspectral Remote Sensing https://creativecommons.org/licenses/by/4.0 Journal of Hyperspectral Remote Sensing; v. 9, n. 4 (2019): Journal of Hyperspectral Remote Sensing; 228-239 2237-2202 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2019 ftunifpernambojs https://doi.org/10.29150/jhrs.v9.4.p228-239 2023-04-18T10:55:54Z É de extrema relevância entender o comportamento da vegetação para o planejamento e tomada de decisão no que se refere as áreas para plantio, uso adequado de recursos hídricos, irrigação e acompanhamento de dinâmicas vegetacionais, por exemplo. Neste sentido, o Sensoriamento Remoto (SR) vem sendo um relevante suporte para o monitoramento de ecossistemas, uma vez que se observa diversas pesquisas envolvendo a aplicação desta técnica através de diferentes algoritmos matemáticos intitulados índices. Os novos satélites, os veículos não tripulados e as câmeras de alta resolução que mantém produtos na faixa do visível (RGB) trazem novas perspectivas para a atuação do SR na vegetação, sobretudo na agricultura; assim, foi desenvolvido ao longo dos anos índices que possibilitasse a detecção da vegetação nas faixas espectrais visíveis e dessa forma, facilitando processos agropastoris, de agricultura de precisão e no barateamento do SR como um todo. Deste modo, este trabalho tem como objetivo uma revisão acerca dos índices de vegetação para o processamento na faixa RGB. A partir da revisão, verifica-se a procedência de quinze índices RGB, sendo concebidos por necessidades e equipamentos diversos, onde todos alcançam satisfatoriedade competida. Contata-se que os índices desenvolvidos melhoraram em significância as análises do SR, e que essas melhorias acarretaram novos aprendizados que contribuíram diretamente para o estudo dos ecossistemas, especialmente os ambientes vegetacionais. O dinamismo do SR o faz chamariz de inovação, em que, através das exigências e de demandas atuais, novos índices poderão ser criados contribuindo na manutenção e provimento de atividades sociais, econômicas e ecológicas. Article in Journal/Newspaper Arctic Portal de Periódicos - UFPE (Universidade Federal de Pernambuco) Alta Journal of Hyperspectral Remote Sensing 9 4 228

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