Abstract
The article presents the material and methods for studying space images based on the analysis of the spectral luminance coefficient (SLC). Based on the data obtained during experiments to obtain numerical values of the SLC, which are published in the open press, patterns of behavior of soil and vegetation reflection processes are revealed, and clustering of multispectral wave distribution ranges is proposed, which can uniquely identify the type of objects under consideration. Since the distribution of plant SLC varies by vegetation period, the above-mentioned clustering of SLC ranges is also proposed for them. It should be noted that the distribution of luminance spectra depends on the climatic and geographical conditions of plant species and is unique for each region. This study is related to the Akmola region, which itself is divided into four zones. The cluster based SLC data reflect the normal development of plant species. If there are deviations, i.e., the SLC does not belong to the cluster, then there is an algorithm that identifies the reason for the deviation and suggests an action plan to eliminate the defect.