Monitoring Corn Nitrogen Concentration from Radar (C-SAR), Optical, and Sensor Satellite Data Fusion

Corn (Zea mays L.) nitrogen (N) management requires monitoring plant N concentration (Nc) with remote sensing tools to improve use, increasing both profitability and sustainability. This work aims predict the corn Nc during growing cycle from Sentinel-2 Sentinel-1 (C-SAR) sensor data fusion. Eleven experiments using five fertilizer rates (0, 60, 120, 180, 240 kg ha−1) were conducted in Pampas region of Argentina. Plant samples collected at four stages vegetative reproductive periods. Vegetation indices calculated new combinations spectral bands, C-SAR backscatters, fusion derived Sentinel-2. Predictive models best fit (R2 = 0.91) calibrated band six experiments. During validation experiments, predicted lower error (MAPE: 14%, RMSE: 0.31 %Nc) than combination 20%, 0.44 %Nc). The red-edge (704, 740, 740 nm), short-wave infrared (1375 nm) VV backscatter all necessary monitor Nc. Thus, satellite via is a critical source for predicting changes status.