REMOTE SENSING AND GEOSTATISTICS APPLIED TO NDVI, KC AND PRODUCTIVE PARAMETERS IN IRRIGATED CORN CROP
DOI:
https://doi.org/10.15809/irriga.2023v28n3p535-544Abstract
REMOTE SENSING AND GEOSTATISTICS APPLIED TO NDVI, KC AND PRODUCTIVE PARAMETERS IN IRRIGATED CORN CROP
PEDRO ROGERIO GIONGO1; DARLENE DE MATOS SANTOS2; TALLITA MAIELLY GONÇALVES DE MOURA NEVES2; ADRIANA RODOLFO DA COSTA1; PATRICIA COSTA SILVA1 E JOSÉ HENRIQUE DA SILVA TAVEIRA1
[1] PhD in science, agronomy, professors at the State University of Goiás, Institute of Agricultural Sciences and Sustainability, Santa Helena de Goiás, GO, Brazil. E-mail: pedro.giongo@ueg.br; adriana.costa@ueg.br; patricia.costa@ueg.br; jose.taveira@ueg.br
2 Agricultural Engineer, State University of Goiás, Santa Helena de Goiás, GO, Brazil. E-mail: darlenematos99@gmail.com; tallita.maielly.35@gmail.com
1 ABSTRACT
Remote sensing (SR) has contributed to digital agriculture, associated with the use of geostatistical techniques that allow data acquisition, analysis and decision making. In view of this, the objective of this work was to evaluate the spatial variability of soil physical attributes, NDVI and second crop corn productivity in the territory of Santa Helena de Goiás, and to estimate values of crop coefficient (KC) through the NDVI, and to evaluate the spatiality. Soil samples were collected in a georeferenced way using a regular grid. The images were from the Sentinel 2A satellite. The Normalized Difference Vegetation Index (NDVI) was calculated, the Kc values of the crop were estimated, using two methodologies Toureiro et al., (2017) and Kamble, Kilic, Hubbard (2013), and later the values were extracted through a regular GRID, with which the geostatistical analyzes and correlations with productivity were submitted. The NDVI showed an increase up to 69 days after planting, in addition to proving the spatial variability and spatial dependence. With the geostatistics it was possible to generate a map of the spatial distribution of productivity. The NDVI allowed to obtain the Kc corresponding to the different phases of cultivation, sensitive to the methodologies used. The Kc obtained presents a high response and potential to the management of irrigated corn.
Keywords: Precision agriculture, Interpolation, Center Pivot.
GIONGO, P. R; SANTOS, D. M.; NEVES, T. M. G. M; COSTA, A. R.; SILVA, P. C.; TAVEIRA, J. H. S.
SENSORIAMENTO REMOTO E GEOESTATISTICA APLICADO A PARAMETROS DE NDVI, KC E PRODUTIVOS NA CULTURA DO MILHO IRRIGADO
2 RESUMO
O sensoriamento remoto (SR) tem contribuído com a agricultura digital, associado ao uso de técnicas de geoestatística que permitem a aquisição de dados, analise e tomada de decisão. Diante disso o objetivo deste trabalho foi avaliar a variabilidade espacial dos atributos físicos do solo, NDVI e produtividade de milho de segunda safra no território de Santa Helena de Goiás, e estimar valores de coeficiente de cultivo (KC) por meio do NDVI, e avaliar a espacialidade. As amostragens de solos foram coletadas de forma georreferenciada por meio de um gride regular. As imagens foram do satélite Sentinel 2A. Foi calculado o Índice de Vegetação da Diferença Normalizada (NDVI), foi estimado os valores de Kc da cultura, por meio de duas metodologias Toureiro et al. (2017) e Kamble, Kilic, Hubbard (2013), e posteriormente foi realizado a extração dos valores através de um GRID regular, com o qual foi submetido as análises de geoestatistica e as correlações com a produtividade. O NDVI apresentou-se crescente até os 69 dias após o plantio, além de comprovar a variabilidade espacial e dependência espacial. Com a geoestatística foi possível gerar o mapa da distribuição espacial da produtividade. O NDVI permitiu obter o Kc correspondente as diferentes fases de cultivo, sensível as metodologias utilizadas. O Kc obtido apresenta uma alta resposta e potencial ao manejo do milho irrigado.
Palavras-chave: Agricultura de precisão, Interpolação, Pivô Central.
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