Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFPE |
dARK ID: | ark:/64986/001300000wrw8 |
Texto Completo: | https://repositorio.ufpe.br/handle/123456789/39702 |
Resumo: | Droughts are one of the most common natural hazards in the world that can affect social and economic aspects. The objectives of this dissertation is: (i) to characterize agricultural drought on Brazilian soybeans producing areas in terms of frequency and severity, during 1983-2016 period, through precipitation anomalies and ENSO Precipitation Index (ESPI) event; (ii) establish the degree of significance between Normalized Difference Vegetation Index (NDVI) and precipitation and (iii) assess the impacts on production drought months with critical soybean yield periods. The data used are NDVI, using the AVHRR and MODIS sensors, monthly precipitation data from the soybean producing states, soybean production data and ESPI events. The methods consist of using the percentiles in conjunction with the time series analysis, the lower threshold percentile of 25% was calculated and 75% represented the highest threshold. The thresholds values are plotted in the time series, identifying extreme dryness and wetness as the two categories. The results of the anomalies pointed out the pluviometric variability throughout Brazil, registering events considered extremely dryness, during consecutive years (1985, 1989, 1990, 1991, 1994, 1995, 1999, 2001, 2002, 2005, 2007, 2011, 2012 and 2015). It is possible to observe that precipitation anomalies followed moderately to soybean production. Then, the precipitation anomalies are correlated with NDVI to demonstrate the efficiency of the index for each soybean production state. The year 2012 recorded the lowest NDVI value, reaching 0.53 and the precipitation anomaly was -0.91, in which it can be observed that the NDVI values are correlated with precipitation. It is compared the years of negative precipitation anomalies under the ESPI phenomenon, it is possible to observe that whenever ESPI obtains negative values it generates significant changes in precipitation patterns. Thus, this research is important for Brazil, as it provides alternatives to monitor and evaluate the impacts of agricultural drought on soybean production. |
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ARAÚJO, Inessa Racine Gomes dehttp://lattes.cnpq.br/5725362131428571http://lattes.cnpq.br/2283319786776203http://lattes.cnpq.br/4763821945825516GONÇALVES, Rodrigo MikoszAWANGE, Joseph2021-04-13T14:11:00Z2021-04-13T14:11:00Z2019-09-02ARAÚJO, Inessa Racine Gomes de. Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI. 2019. Dissertação (Mestrado em Ciências Geodésicas e Tecnologias da Geoinformação) - Universidade Federal de Pernambuco, Recife, 2019.https://repositorio.ufpe.br/handle/123456789/39702ark:/64986/001300000wrw8Droughts are one of the most common natural hazards in the world that can affect social and economic aspects. The objectives of this dissertation is: (i) to characterize agricultural drought on Brazilian soybeans producing areas in terms of frequency and severity, during 1983-2016 period, through precipitation anomalies and ENSO Precipitation Index (ESPI) event; (ii) establish the degree of significance between Normalized Difference Vegetation Index (NDVI) and precipitation and (iii) assess the impacts on production drought months with critical soybean yield periods. The data used are NDVI, using the AVHRR and MODIS sensors, monthly precipitation data from the soybean producing states, soybean production data and ESPI events. The methods consist of using the percentiles in conjunction with the time series analysis, the lower threshold percentile of 25% was calculated and 75% represented the highest threshold. The thresholds values are plotted in the time series, identifying extreme dryness and wetness as the two categories. The results of the anomalies pointed out the pluviometric variability throughout Brazil, registering events considered extremely dryness, during consecutive years (1985, 1989, 1990, 1991, 1994, 1995, 1999, 2001, 2002, 2005, 2007, 2011, 2012 and 2015). It is possible to observe that precipitation anomalies followed moderately to soybean production. Then, the precipitation anomalies are correlated with NDVI to demonstrate the efficiency of the index for each soybean production state. The year 2012 recorded the lowest NDVI value, reaching 0.53 and the precipitation anomaly was -0.91, in which it can be observed that the NDVI values are correlated with precipitation. It is compared the years of negative precipitation anomalies under the ESPI phenomenon, it is possible to observe that whenever ESPI obtains negative values it generates significant changes in precipitation patterns. Thus, this research is important for Brazil, as it provides alternatives to monitor and evaluate the impacts of agricultural drought on soybean production.CAPESAs secas são um dos riscos naturais mais comuns no mundo que podem afetar aspectos sociais e econômicos. Os objetivos desta dissertação são (i) caracterizar a seca agrícola nas áreas produtoras de soja do Brasil em termos de frequência e gravidade, durante o período 1983-2016, através de anomalias de precipitação e Índice de Precipitação (ESPI) (ii) estabelecer o grau de significância entre o Índice de Vegetação por Diferença Normalizada (NDVI) e as anomalias de precipitação (iii) avaliar os impactos na produção dos meses de seca com os períodos críticos de produtividade da soja. Os dados utilizados são o NDVI, utilizando os sensores AVHRR e MODIS, os dados mensais de precipitação dos estados produtores de soja, os dados de produção de soja e dos eventos do ESPI. Os métodos consistem em utilizar os percentis em conjunto com a análise de séries temporais, foi calculado o percentil do limiar inferior de 25% e 75% representou o limiar superior. O valor limite foi então plotado na série temporal, identificando seca extrema e umidade como as duas categorias. Os resultados das anomalias apontam para a existência de grande variabilidade pluviométrica em todo o Brasil, registrando eventos considerados extremamente secos, durante anos consecutivos (1985, 1989, 1990, 1991, 1994, 1995, 1999, 2001, 2002, 2005, 2007, 2011, 2012 e 2015), foi possível observar que as anomalias de precipitação responderam moderadamente à produção de soja. Em seguida as anomalias de precipitação foram correlacionadas com NDVI para demonstrar a eficiência do índice, os valores analisados correspondem à localização da produção de soja para cada Estado. O ano de 2012 registrou o menor valor de NDVI, chegando a 0,53 e a anomalia de precipitação foi de -0,91, no qual pode-se observar que os valores de NDVI responderam bem à precipitação. Foram comparados os anos de anomalias de precipitação negativas sob a influência do fenômeno ESPI, sendo possível observar que sempre que o ESPI obtém valores negativos gera mudanças significativas nos padrões de precipitação. Assim, esta pesquisa é importante para o Brasil, pois fornecem alternativas para monitorar e avaliar os impactos da seca agrícola na produção de soja.engUniversidade Federal de PernambucoPrograma de Pos Graduacao em Ciencias Geodesicas e Tecnologias da GeoinformacaoUFPEBrasilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessCiências geodésicas e tecnologias da geoinformaçãoAnomalias de precipitaçãoNDVISecaSojaDetection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPIinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesismestradoreponame:Repositório Institucional da UFPEinstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPEORIGINALDISSERTAÇÃO Inessa Racine Gomes de Araújo.pdfDISSERTAÇÃO Inessa Racine Gomes de Araújo.pdfapplication/pdf2021420https://repositorio.ufpe.br/bitstream/123456789/39702/1/DISSERTA%c3%87%c3%83O%20Inessa%20Racine%20Gomes%20de%20Ara%c3%bajo.pdf847cd3397e0116a3b4303b7aecbf0153MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.pt_BR.fl_str_mv |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
title |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
spellingShingle |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI ARAÚJO, Inessa Racine Gomes de Ciências geodésicas e tecnologias da geoinformação Anomalias de precipitação NDVI Seca Soja |
title_short |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
title_full |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
title_fullStr |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
title_full_unstemmed |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
title_sort |
Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI |
author |
ARAÚJO, Inessa Racine Gomes de |
author_facet |
ARAÚJO, Inessa Racine Gomes de |
author_role |
author |
dc.contributor.authorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/5725362131428571 |
dc.contributor.advisorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/2283319786776203 |
dc.contributor.advisor-coLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/4763821945825516 |
dc.contributor.author.fl_str_mv |
ARAÚJO, Inessa Racine Gomes de |
dc.contributor.advisor1.fl_str_mv |
GONÇALVES, Rodrigo Mikosz |
dc.contributor.advisor-co1.fl_str_mv |
AWANGE, Joseph |
contributor_str_mv |
GONÇALVES, Rodrigo Mikosz AWANGE, Joseph |
dc.subject.por.fl_str_mv |
Ciências geodésicas e tecnologias da geoinformação Anomalias de precipitação NDVI Seca Soja |
topic |
Ciências geodésicas e tecnologias da geoinformação Anomalias de precipitação NDVI Seca Soja |
description |
Droughts are one of the most common natural hazards in the world that can affect social and economic aspects. The objectives of this dissertation is: (i) to characterize agricultural drought on Brazilian soybeans producing areas in terms of frequency and severity, during 1983-2016 period, through precipitation anomalies and ENSO Precipitation Index (ESPI) event; (ii) establish the degree of significance between Normalized Difference Vegetation Index (NDVI) and precipitation and (iii) assess the impacts on production drought months with critical soybean yield periods. The data used are NDVI, using the AVHRR and MODIS sensors, monthly precipitation data from the soybean producing states, soybean production data and ESPI events. The methods consist of using the percentiles in conjunction with the time series analysis, the lower threshold percentile of 25% was calculated and 75% represented the highest threshold. The thresholds values are plotted in the time series, identifying extreme dryness and wetness as the two categories. The results of the anomalies pointed out the pluviometric variability throughout Brazil, registering events considered extremely dryness, during consecutive years (1985, 1989, 1990, 1991, 1994, 1995, 1999, 2001, 2002, 2005, 2007, 2011, 2012 and 2015). It is possible to observe that precipitation anomalies followed moderately to soybean production. Then, the precipitation anomalies are correlated with NDVI to demonstrate the efficiency of the index for each soybean production state. The year 2012 recorded the lowest NDVI value, reaching 0.53 and the precipitation anomaly was -0.91, in which it can be observed that the NDVI values are correlated with precipitation. It is compared the years of negative precipitation anomalies under the ESPI phenomenon, it is possible to observe that whenever ESPI obtains negative values it generates significant changes in precipitation patterns. Thus, this research is important for Brazil, as it provides alternatives to monitor and evaluate the impacts of agricultural drought on soybean production. |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019-09-02 |
dc.date.accessioned.fl_str_mv |
2021-04-13T14:11:00Z |
dc.date.available.fl_str_mv |
2021-04-13T14:11:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
dc.identifier.citation.fl_str_mv |
ARAÚJO, Inessa Racine Gomes de. Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI. 2019. Dissertação (Mestrado em Ciências Geodésicas e Tecnologias da Geoinformação) - Universidade Federal de Pernambuco, Recife, 2019. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufpe.br/handle/123456789/39702 |
dc.identifier.dark.fl_str_mv |
ark:/64986/001300000wrw8 |
identifier_str_mv |
ARAÚJO, Inessa Racine Gomes de. Detection of agricultural drought impacts on soybeans production in Brazil (1983-2016) using precipitation anomalies, NDVI and ESPI. 2019. Dissertação (Mestrado em Ciências Geodésicas e Tecnologias da Geoinformação) - Universidade Federal de Pernambuco, Recife, 2019. ark:/64986/001300000wrw8 |
url |
https://repositorio.ufpe.br/handle/123456789/39702 |
dc.language.iso.fl_str_mv |
eng |
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eng |
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http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pos Graduacao em Ciencias Geodesicas e Tecnologias da Geoinformacao |
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UFPE |
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Universidade Federal de Pernambuco |
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