Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the SD, the difference in the maturation cycles of the cultivars, and regional climatic variation, the HD of soybean varied greatly during the studied crop years, ranging from mid-February to late March. The SD of corn is before that of soybean, and mainly occurs in late September to mid-October. The DMVD mainly occurs during December, and the HD is distributed throughout January to March in Paraná. When comparing the estimated dates with observed dates the mean error (ME) varied from 0.2 days earlier to 3.3 days after the observed date for soybean with root mean square error (RMSE) from 1.93 to 14.73 days. For corn, the ME varied from 10.3 days to 18.5 days after the observed date with RMSE from 18.02 to 27.82 days.
The use of effective technologies for the monitoring of agricultural crops should seek methodologies that provide information regarding crop development, preferably before harvesting. The study of the monitoring and/or estimation of areas using vegetation indices derived from multitemporal data from MODIS sensors is being studied in the search for greater objectivity of the generated values. In this context, the objective of this study was to map areas with winter and second-crop corn using EVI/MODIS time series from the Terra and Aqua satellites, for the seasons from 2012 to 2014 in the Paraná state of Brazil. Accuracy analysis of the mappings was performed in spatial resolution images of 30 m (LISS-III and Landsat-8), to identify and validate the masks the crops of interest. The accuracy of the mapping obtained values of global precision 87.5%, 79.5%, and 82.0%, with Kappa index of 0.81, 0.69, and 0.73, in the 2012, 2013, and 2014 harvests, respectively. Comparing with data from the Brazilian Institute of Geography and Statistics (IBGE), the areas obtained by the mappings were underestimated for the second-crop corn in the 2012 and 2013 seasons and overestimated in 2014. The winter crops were overestimated for the three seasons investigated. The use of remote sensing data and techniques can contribute to a quick estimation of crop area information, and can assist in the surveys conducted by official institutions.
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