Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/42839
metadata.artigo.dc.title: A spectral agrometeorological model for estimating soybean grain productivity in Mato Grosso, Brazil
metadata.artigo.dc.creator: Sarmiento, Christiany Mattioli
Coltri, Priscila Pereira
Alves, Marcelo de Carvalho
Carvalho, Luiz Gonsaga de
metadata.artigo.dc.subject: Geographic information system
Mathematical modeling
Remote sensing
Agrometeorology
Crop monitoring
Sistema de informação geográfica
Modelagem matemática
Sensoriamento remoto
Agrometeorologia
Monitoramento de safra
Soja - Produtividade
metadata.artigo.dc.publisher: Associação Brasileira de Engenharia Agrícola
metadata.artigo.dc.date.issued: Jun-2020
metadata.artigo.dc.identifier.citation: SARMIENTO, C. M. et al. A spectral agrometeorological model for estimating soybean grain productivity in Mato Grosso, Brazil. Engenharia Agrícola, Jaboticabal, v. 40, n. 3, p. 405-412, mai./jun. 2020. DOI: http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v40n3p405-412/2020.
metadata.artigo.dc.description.abstract: This study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index – NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to estimate production and productivity in the study area. Willmott's agreement index was 0.99 and 0.96 and Pearson's correlation coefficient was 0.99 and 0.84 for production and productivity, respectively.
metadata.artigo.dc.identifier.uri: http://repositorio.ufla.br/jspui/handle/1/42839
metadata.artigo.dc.language: en
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