Abstract
Using satellite imagery, this study investigates the spectral reflectance characteristics of crops at the OHMK farm in Eastern Kazakhstan, focusing on wheat and barley. The analysis reveals significant differences in spectral re- flectance, particularly in the visible and near-infrared regions, and tracks change over time during different growth stages. Employing principal component analysis (PCA), strong correlations are observed between specific spectral bands and principal components, providing insights into crop variability. Derived equations enable the estimation of principal component values based on spectral information. These findings have implications for crop monitoring, management, and precision agriculture, offering potential yield optimization and resource allocation improvements. The study highlights the potential use of spectral reflectance analysis for crop health assessment and yield prediction, with implications for agricultural decision-making and enhanced productivity. Further research is needed to expand the application of this approach to other crops and conditions.