Anibal Gusso

Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil

Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, with R 2 = 0.97 and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.

Monitoring the vulnerability of soybean to heat waves and their impacts in Mato Grosso state, Brazil

Increases in the frequency of extreme events, such as the occurrence of high temperatures, are prone to produce severe effects on summer crop yields especially soybeans and maize. Under a climate change scenario, the physical parameters of the Earths surface, such as temperature, water availability and evapotranspiration, are expected to change over the next decades. We investigated the variability of soybean yields associated with crop canopy temperatures during key development that are sensitive to the occurrence of high temperatures in Mato Grosso State, Brazil. In the present paper, we propose that the temperature fluctuations around the optimum level in the crop canopy can cause favorable effects on soybean yields in MT State/Brazil. In order to evaluate the above mentioned hypothesis, we investigated the effects of canopy temperature on soybean yield during flowering to the grain filling periods using Aqua and Terra/MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data, between 2003 and 2010. Comparison of spatially interpolated maps show that yield variations are positively related to canopy-LST during of flowering period, with R2=0.60 and RMSD=6.2%. Overall results show that increases in canopy-LST temperature in Mato Grosso State, during flowering/grain filling periods, are related to higher soybean yield averages.