Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes

Detalhes bibliográficos
Autor(a) principal: Dutra, Débora Joana
Data de Publicação: 2021
Outros Autores: Elmiro, Marcos Antônio Timbó, Coelho, Carlos Wagner Gonçalves Andrade, Nero, Marcelo Antônio, Temba, Plínio da Costa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Sociedade & natureza (Online)
Texto Completo: https://seer.ufu.br/index.php/sociedadenatureza/article/view/59505
Resumo: The development of several time series analysis programs using satellite images has provided many applications based on resources from geostatistics field. Currently, the use of statistical tests applied to vegetation indexes has enabled the analysis of different natural phenomena, such as drought events in watershed areas. The objective of this article is to provide a comparative analysis between NDVI and EVI vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG. The methodology adopted the Cox-Stuart statistical test for seasonality analysis and Pearson's linear correlation to verify the influence of different indexes on delimitation of drought in a watershed. The results indicated the NDVI vegetation index as more efficient than EVI in spatial characterization of studied watershed region, mainly in identification of seasonality. The VCI proved to be highly feasible for monitoring drought in study period between 2013 and 2018, allowing the effective delimitation of drought conditions in the Serra Azul stream sub-basin. In addition, the effectiveness of MODIS sensor data in characterizing drought events that affected the study area was proven.
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spelling Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexesGeoestatísticaSensoriamento remotoSazonalidadeÍndice de secaÍndice de vegetaçãoGeostatisticsRemote sensingSeasonalityDrought indexVegetation indexThe development of several time series analysis programs using satellite images has provided many applications based on resources from geostatistics field. Currently, the use of statistical tests applied to vegetation indexes has enabled the analysis of different natural phenomena, such as drought events in watershed areas. The objective of this article is to provide a comparative analysis between NDVI and EVI vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG. The methodology adopted the Cox-Stuart statistical test for seasonality analysis and Pearson's linear correlation to verify the influence of different indexes on delimitation of drought in a watershed. The results indicated the NDVI vegetation index as more efficient than EVI in spatial characterization of studied watershed region, mainly in identification of seasonality. The VCI proved to be highly feasible for monitoring drought in study period between 2013 and 2018, allowing the effective delimitation of drought conditions in the Serra Azul stream sub-basin. In addition, the effectiveness of MODIS sensor data in characterizing drought events that affected the study area was proven.A criação de diversos programas de análise de séries temporais, por meio do uso de imagens de satélite, tem permitido diversas aplicações dentro do campo da geoestatística. Atualmente, o uso de testes estatísticos aplicados aos índices de vegetação tem possibilitado a análise de diversos fenômenos naturais, como eventos de secas em bacias hidrográficas. Assim, o objetivo deste artigo foi fornecer uma análise comparativa entre os dados do projeto MOD13Q1 do sensor MODIS, referentes aos índices de vegetação NDVI e EVI para mapeamento de seca por meio da utilização do índice de condição de vegetação (ICV) na sub-bacia do ribeirão Serra Azul, MG. A metodologia utilizada envolveu o uso do teste estatístico de Cox-Stuart para análise de sazonalidade e o uso de correlação linear para verificação de influência dos índices na delimitação de seca em uma bacia hidrográfica. Os resultados demonstraram que entre os índices de vegetação, o NDVI mostrou-se mais eficiente na caracterização da região espacial da sub-bacia do que o EVI, principalmente em relação à identificação da sazonalidade. Além disso, o ICV se mostrou altamente viável para o monitoramento da seca / estiagem nos períodos de estudo entre 2013 e 2018, permitindo a delimitação efetiva dos estados de seca na sub-bacia do Ribeirão Serra Azul. Por fim, os dados do sensor MODIS provaram sua eficácia na caracterização da seca na bacia hidrográfica de estudo.  Universidade Federal de Uberlândia2021-06-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/sociedadenatureza/article/view/5950510.14393/SN-v33-2021-59505Sociedade & Natureza; Vol. 33 (2021)Sociedade & Natureza; v. 33 (2021)1982-45130103-1570reponame:Sociedade & natureza (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/sociedadenatureza/article/view/59505/31809Copyright (c) 2021 Débora Joana Dutra, Marcos Antônio Timbó Elmiro, Carlos Wagner Gonçalves Andrade Coelho, Marcelo Antônio Nero, Plínio da Costa Tembainfo:eu-repo/semantics/openAccessDutra, Débora JoanaElmiro, Marcos Antônio Timbó Coelho, Carlos Wagner Gonçalves Andrade Nero, Marcelo Antônio Temba, Plínio da Costa 2021-07-28T18:28:11Zoai:ojs.www.seer.ufu.br:article/59505Revistahttp://www.sociedadenatureza.ig.ufu.br/PUBhttps://seer.ufu.br/index.php/sociedadenatureza/oai||sociedade.natureza.ufu@gmail.com|| lucianamelo@ufu.br1982-45130103-1570opendoar:2021-07-28T18:28:11Sociedade & natureza (Online) - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
title Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
spellingShingle Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
Dutra, Débora Joana
Geoestatística
Sensoriamento remoto
Sazonalidade
Índice de seca
Índice de vegetação
Geostatistics
Remote sensing
Seasonality
Drought index
Vegetation index
title_short Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
title_full Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
title_fullStr Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
title_full_unstemmed Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
title_sort Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
author Dutra, Débora Joana
author_facet Dutra, Débora Joana
Elmiro, Marcos Antônio Timbó
Coelho, Carlos Wagner Gonçalves Andrade
Nero, Marcelo Antônio
Temba, Plínio da Costa
author_role author
author2 Elmiro, Marcos Antônio Timbó
Coelho, Carlos Wagner Gonçalves Andrade
Nero, Marcelo Antônio
Temba, Plínio da Costa
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Dutra, Débora Joana
Elmiro, Marcos Antônio Timbó
Coelho, Carlos Wagner Gonçalves Andrade
Nero, Marcelo Antônio
Temba, Plínio da Costa
dc.subject.por.fl_str_mv Geoestatística
Sensoriamento remoto
Sazonalidade
Índice de seca
Índice de vegetação
Geostatistics
Remote sensing
Seasonality
Drought index
Vegetation index
topic Geoestatística
Sensoriamento remoto
Sazonalidade
Índice de seca
Índice de vegetação
Geostatistics
Remote sensing
Seasonality
Drought index
Vegetation index
description The development of several time series analysis programs using satellite images has provided many applications based on resources from geostatistics field. Currently, the use of statistical tests applied to vegetation indexes has enabled the analysis of different natural phenomena, such as drought events in watershed areas. The objective of this article is to provide a comparative analysis between NDVI and EVI vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG. The methodology adopted the Cox-Stuart statistical test for seasonality analysis and Pearson's linear correlation to verify the influence of different indexes on delimitation of drought in a watershed. The results indicated the NDVI vegetation index as more efficient than EVI in spatial characterization of studied watershed region, mainly in identification of seasonality. The VCI proved to be highly feasible for monitoring drought in study period between 2013 and 2018, allowing the effective delimitation of drought conditions in the Serra Azul stream sub-basin. In addition, the effectiveness of MODIS sensor data in characterizing drought events that affected the study area was proven.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-10
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://seer.ufu.br/index.php/sociedadenatureza/article/view/59505
10.14393/SN-v33-2021-59505
url https://seer.ufu.br/index.php/sociedadenatureza/article/view/59505
identifier_str_mv 10.14393/SN-v33-2021-59505
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/sociedadenatureza/article/view/59505/31809
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Uberlândia
publisher.none.fl_str_mv Universidade Federal de Uberlândia
dc.source.none.fl_str_mv Sociedade & Natureza; Vol. 33 (2021)
Sociedade & Natureza; v. 33 (2021)
1982-4513
0103-1570
reponame:Sociedade & natureza (Online)
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Sociedade & natureza (Online)
collection Sociedade & natureza (Online)
repository.name.fl_str_mv Sociedade & natureza (Online) - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv ||sociedade.natureza.ufu@gmail.com|| lucianamelo@ufu.br
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