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

Narin O. G. , ABDİKAN S.

GEOCARTO INTERNATIONAL, vol.37, no.5, pp.1378-1392, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1080/10106049.2020.1765886
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Environment Index, Geobase, INSPEC
  • Page Numbers: pp.1378-1392
  • Keywords: yield estimation, vegetation index, BBCH-Scale, Sentinel-2, sunflower plant, LEAF-AREA INDEX, SPECTRAL REFLECTANCE, VEGETATION INDEXES, CORN
  • Hacettepe University Affiliated: Yes


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.