Remote sensing data and machine learning to predict yields of major crops on regional scale.

Abstract

Remote sensing and machine learning tandem is a powerful tool for crop monitoring and yield prediction. Current study is devoted to the evaluation of the relationship between five remote sensing indicators, affecting crop yields, such as NDVI, NDMI, VHI, LST and PET, as well as establishing the connectivity of these indices with the yields of twelve major crops cultivated in Ukraine during the period 2015-2023. Yielding data were retrieved form official statistical bodies of Ukraine.