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Conference object . 2017 . Peer-reviewed
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Conference object . 2017
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Variación espacio-temporal de la fenología del arroz en Aragón a partir de información multiespectral satelital

Authors: Guillén, Mónica; Moreno-García, Beatriz; Quílez Sáez de Viteri, Dolores; Casterad Seral, María Auxiliadora;

Variación espacio-temporal de la fenología del arroz en Aragón a partir de información multiespectral satelital

Abstract

[ES] El manejo de los cultivos exige conocer su fenología anual para poder establecer los momentos adecuados en los que llevar a cabo diferentes actuaciones durante la campaña agrícola. Las imágenes multiespectrales son una fuente de información que se está incorporando en herramientas de ayuda a la toma de decisiones en agricultura. El propósito de este trabajo es conocer la variación espacio-temporal de la fenología del arroz en Aragón para decidir las fechas idóneas de adquisición de imágenes a partir de las cuales se pueda diseñar una herramienta de ayuda a la toma de decisiones en la aplicación de la fertilización nitrogenada. Para ello se construyen y comparan series temporales de NDVI obtenidas, según los años, de imágenes Landsat o Deimos, con las que se caracteriza el ciclo fenológico del arroz en siete localidades distribuidas en las zonas arroceras de Aragón durante el periodo 2008-2013. Los resultados obtenidos muestran que el desarrollo del cultivo fue similar todos los años, excepto en 2013 debido a condiciones meteorológicas adversas después de la siembra. Además, no parecen existir diferencias de ciclo entre las distintas localidades, a excepción de Ejea de los Caballeros con un desarrollo inicial del cultivo más lento. Esta uniformidad de ciclos del cultivo simplifica y abarata la adquisición de la información espectral al no precisarse de imágenes en fechas diferentes para cada localidad.

[EN] The knowledge of crop phenology is necessary to establish the right times to carry out agricultural activities during the growing season. Multispectral images provide relevant crop information and are being incorporated into decision support tools in agriculture. The objective of this work was to study the spatio-temporal variation of rice phenology in Aragon to determine suitable dates for the acquisition of images for the design of a decision support tool for N topdressing recommendations. To achieve this objective, series of NDVI (from Landsat or Deimos depending on the year) were built and compared to characterize rice phenological cycle in seven locations distributed in the rice-growing areas of Aragon in the years 2008 to 2013. The results showed that the crop development was similar between years, except in 2013 due to adverse meteorological conditions after sowing. Moreover, phenological cycles in the different locations were similar, except for Ejea de los Caballeros where the initial crop development was lengthier. This uniformity in crop development could simplify and reduce the cost of the acquisition of the spectral information since it is not necessary to obtain images at different dates for each location.

Este trabajo forma parte de actividades desarrolladas en los proyectos RTA2010-00126 y RTA20130-0057-C04.

4 pags.- 2 Figs.

Peer reviewed

Country
Spain
Related Organizations
Keywords

Fenología, Deimos, Phenology, Arroz, NDVI, Rice, Landsat

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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