Estimation and Prediction of Cereal Production Using Normalized Difference Vegetation Index Time Series (Sentinel-2) Data in Central Spain †

Abstract

Estimating production in cereal fields allows farmers to obtain information on improving management in their following campaigns and avoiding losses. The main objective of this work was to estimate grain production in cereals (wheat and barley) in the 2019 and 2020 campaigns in three provinces of Central Spain. The model was based on the prediction of the maximum values of the Sentinel-2 Normalized Difference Vegetation Index (NDVI) time series with ARIMA and multiple linear regression models. The highest correlation was found between grain yield and the variables’ five-month cumulative rainfall and maximum greenness (NDVImax).