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Provedor de dados:  REA
País:  Brazil
Título:  VEGETATION INDICES FOR IRRIGATED CORN MONITORING
Autores:  Alvino,Francisco C. G.
Aleman,Catariny C.
Filgueiras,Roberto
Althoff,Daniel
da Cunha,Fernando F.
Data:  2020-06-01
Ano:  2020
Palavras-chave:  Vegetation cover
Decision-making
Remote sensing
Resumo:  ABSTRACT Monitoring of large agricultural lands is often hampered by data collection logistics at field level. To solve such a problem, remote sensing techniques have been used to estimate vegetation indices, which can subsidize crop management decision-making. Therefore, this study aimed to select vegetation indices to detect variability in irrigated corn crops. Data were collected in São Desidério, Bahia State (Brazil), using an OLI sensor (Operational Land Imager) embedded to a Landsat-8 satellite platform. Five corn growing plots under central pivot irrigation were assessed. The following vegetation indices were tested: NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), SAVI (Soil Adjusted Vegetation Index), GNDVI (Green Normalized Difference Vegetation Index), SR (Simple Ratio), NDWI (Normalized Difference Water Index), and MSI (Moisture Stress Index). Among the tested indices, SR was more sensitive to high corn biomass, while GNDVI, NDVI, EVI, and SAVI were more sensitive to low values. Overall, all indices were found to be concordant with each other, with high correlations among them. Despite this, the use of a set of these indices is advisable since some respond better to certain peculiarities than others.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000300322
Editor:  Associação Brasileira de Engenharia Agrícola
Relação:  10.1590/1809-4430-eng.agric.v40n3p322-333/2020
Formato:  text/html
Fonte:  Engenharia Agrícola v.40 n.3 2020
Direitos:  info:eu-repo/semantics/openAccess
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