Use of NDVI/AVHRR time-series profiles for soybean crop monitoring in Brazil
J Esquerdo, J Zullo Júnior… - International Journal of …, 2011 - Taylor & Francis
International Journal of Remote Sensing, 2011•Taylor & Francis
In Brazil there is a need for less subjective, more efficient and less expensive methodologies
for crop yield forecast. Owing to the continental dimensions of the country, orbital images
have been used to estimate the productive potential of crops. In this study, NDVI
(Normalized Difference Vegetation Index) time-series, derived from AVHRR/NOAA
(Advanced Very High Resolution Radiometer/National Oceanic and Atmospheric
Administration) imagery were used for the soybean crop monitoring in a large production …
for crop yield forecast. Owing to the continental dimensions of the country, orbital images
have been used to estimate the productive potential of crops. In this study, NDVI
(Normalized Difference Vegetation Index) time-series, derived from AVHRR/NOAA
(Advanced Very High Resolution Radiometer/National Oceanic and Atmospheric
Administration) imagery were used for the soybean crop monitoring in a large production …
In Brazil there is a need for less subjective, more efficient and less expensive methodologies for crop yield forecast. Owing to the continental dimensions of the country, orbital images have been used to estimate the productive potential of crops. In this study, NDVI (Normalized Difference Vegetation Index) time-series, derived from AVHRR/NOAA (Advanced Very High Resolution Radiometer/National Oceanic and Atmospheric Administration) imagery were used for the soybean crop monitoring in a large production region in Brazil in the 2002/2003 and 2003/2004 cropping seasons. NDVI temporal profiles describing the biomass condition of crops throughout the phenological stages were generated in 18 municipalities. Quantitative parameters were measured from the temporal profiles, based on the full time or partial phenological cycle. Linear regressions between the quantitative parameters and the municipal average yields in both seasons have shown that the most significant correlations occurred when the full time period was considered. When considering periods prior to harvest, the correlations showed a tendency to decline. The NDVI monitoring during these two cropping seasons, which presented different weather conditions, could explain a major part of the soybean yield variability at the municipal level. Results showed the potential of the NDVI time-series analysis in generating parameters to be employed by agrometeorological–spectral models for soybean yield estimations. The automatic system for temporal profiles generation developed in this study sped up the analysis and can be used for further studies at a regional scale.
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