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

Abstract

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 (R2) 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 (R2 = 0.74 and RMSE = 10.80 kg/da) approximately three months before the harvest of sunflower.

Plant phenotyping relevance

Sentinel-2画像と植生指数を用いてヒマワリの生育段階と収量を推定し、精度指標で評価しており、植物形質取得手法の適用・検証が中心です。

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