Monitoring of phenological stage and yield estimation of sunflower plant using Sentinel-2 satellite images

With the increase of the world's population, while urbanization is increasing, agricultural lands are decreasing. Therefore, monitoring of up-to-date agricultural lands is important for agricultural product estimation. The study investigates suitability of Sentinel-2 data for the phenological stage analysis and yield estimation of sunflower plant. To this aim, fieldworks was conducted and sunflower parcels were identified in Zile district of Tokat province, Turkey which has dense sunflower production. In this study, ten Vegetation Indices (VIs) were performed by using multi-temporal Sentinel-2 data obtained during the growth stages of sunflower plant and yield estimation was obtained. As a result, the indices obtained on 30 June, at the stage of inflorescence emergence, provided coefficient of determination (R-2) higher than 0.67 and The Root Mean Square Error (RMSE) lower than 13 kg/da. Among the VIs, the best forecast obtained by NDVI (R-2 = 0.74 and RMSE = 10.80 kg/da) approximately three months before the harvest of sunflower.

Automated summary

With the increasing world population and urbanization, agricultural lands are decreasing, making the monitoring of agricultural lands crucial for crop estimation. This study investigated the suitability of Sentinel-2 data for analyzing the growth stages and estimating the yield of sunflower plants. The results showed that the indices obtained on June 30, during the inflorescence emergence stage, had a coefficient of determination (R-2) higher than 0.67 and a Root Mean Square Error (RMSE) lower than 13 kg/da. Among the Vegetation Indices (VIs), NDVI provided the best forecast three months before the harvest of sunflower.