Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming

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Precision agriculture (PA) aims to identify crop  and soil variability to improve management and optimize the use of inputs. Yield maps become a  relevant tool for PA planning. Vegetation indices (VI) from remote sensing allow monitoring the spatio-temporal variation of crops in the growing  season....

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Autores principales: Ovando, Gustavo, de la Casa, Antonio, Díaz, Guillermo, Díaz, Pablo, Bressanini, Luciano, Miranda, Cristian
Formato: Artículo revista
Lenguaje:Español
Publicado: Facultad de Ciencias Agropecuarias. Área de Difusión Científica 2021
Materias:
Teledetección
mapa de rendimiento
coeficiente de correlaci´ón lineal de Pearson
remote sensing
yield map
Pearson linear correlation coefficient
Acceso en línea:https://revistas.unc.edu.ar/index.php/agris/article/view/25148
Aporte de:
Revistas de la UNC de Universidad Nacional de Córdoba
id I10-R10article-25148
record_format ojs
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-10
container_title_str Revistas de la UNC
language Español
format Artículo revista
topic Teledetección
mapa de rendimiento
coeficiente de correlaci´ón lineal de Pearson
remote sensing
yield map
Pearson linear correlation coefficient
spellingShingle Teledetección
mapa de rendimiento
coeficiente de correlaci´ón lineal de Pearson
remote sensing
yield map
Pearson linear correlation coefficient
Ovando, Gustavo
de la Casa, Antonio
Díaz, Guillermo
Díaz, Pablo
Bressanini, Luciano
Miranda, Cristian
Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming
topic_facet Teledetección
mapa de rendimiento
coeficiente de correlaci´ón lineal de Pearson
remote sensing
yield map
Pearson linear correlation coefficient
author Ovando, Gustavo
de la Casa, Antonio
Díaz, Guillermo
Díaz, Pablo
Bressanini, Luciano
Miranda, Cristian
author_facet Ovando, Gustavo
de la Casa, Antonio
Díaz, Guillermo
Díaz, Pablo
Bressanini, Luciano
Miranda, Cristian
author_sort Ovando, Gustavo
title Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming
title_short Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming
title_full Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming
title_fullStr Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming
title_full_unstemmed Performance of different Sentinel-2A vegetation indices to estimate soybean yield in precision farming
title_sort performance of different sentinel-2a vegetation indices to estimate soybean yield in precision farming
description Precision agriculture (PA) aims to identify crop  and soil variability to improve management and optimize the use of inputs. Yield maps become a  relevant tool for PA planning. Vegetation indices (VI) from remote sensing allow monitoring the spatio-temporal variation of crops in the growing  season. The objective of this work was to evaluate the performance of different Sentinel-2A VIs to estimate soybean (Glycine max (L.) Merril) yield within the framework of PA. The study was carried out using a soybean yield map during the  2017/2018 season from a plot located to the south of Córdoba city, Argentina. Every two bands were taken from a Sentinel-2A image from 4/Feb/2018  and VI were calculated using differences, ratios  and normalized differences. The absolute value of  the Pearson linear correlation coefficient (|r|) between the different IVs and soybean yield was computed. The highest value of |r| (0.726) corresponded to the difference between bands 8  (NIR) and 12 (SWIR), allowing to reproduce with sufficient precision the spatial variability of yields in the plot. 
publisher Facultad de Ciencias Agropecuarias. Área de Difusión Científica
publishDate 2021
url https://revistas.unc.edu.ar/index.php/agris/article/view/25148
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