Budayné Bódi, ErikaOrazalina, Zhaniya2021-05-052021-05-052021-04-22http://hdl.handle.net/2437/308548This study develops a general methodology based on the use of high-resolution remote sensing data to obtain accurate estimates of carrots and yields at the farm level in Tedej, Hungary. The normalized difference vegetation index (NDVI) was used to compare with yield data for selected plants (soybean, winter wheat, maize) as predictors. The study compared the NDVI values with the harvested yield provided by the farm from 2016 to 2018. Late summer and early autumn months are not only critical months for soybean growth but also clear indicators of yield. Implementing accurate methods of data acquisition across the farm improves yield forecasts for future adaptation to climate change. The results provide simple models for forecasting yields as well as forecasting yields for the near future based on freely available satellite data.66ensentinel-2yield predictionndviDEENK Témalista::Mezőgazdaságtudomány