A brief description and the results of experimental testing of a technique for automated processing and analyzing multispectral satellite images of medium and high spatial resolution with the aim of detecting and assessing the dynamics of large logging areas in the territory of the Republic of Kazakhstan are presented. More than 50 large logging areas of about 100 hectares were detected in the selected monitoring site (district of Kokshetau, Akmola territory).

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The paper considers an algorithm for automated classification of mobile small size objects on multispectral satellite images of submeter spatial resolution using radiometric and geometric features. It ensures recognizing the desired classes of objects with high accuracy regardless of their orientation in the image. The geometric features of the objects classified in the binary image included the area of the object, the lengths of the principal and auxiliary axes of inertia, the eccentricity of the ellipse with the main moments of inertia, the area of a convex polygon described near the object, the equivalent diameter of a circle with the same area, and the convexity coefficient.

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