Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
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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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 |
_version_ |
1799943981626294272 |