A control pixel clustering algorithm for assessing the chemical pollution impact on forest tracts from satellite photographic images

The paper proposes an original adaptive control pixel clustering algorithm for "controlled cluster analysis" of satellite photographic images. The "controlled cluster analysis" algorithm is based on the premise: the possibility of using additional a priori information about control pixels on satellite photographs located in different ecological zones, which allows correcting the mosaic structures and ecological zone areas taking into account additional information. The "controlled cluster analysis" algorithm differs in using additional parameters in the form of weight coefficients and control pixels, which provides more accurate binding of clustering results to ecological zones. The "controlled cluster analysis" algorithm is based on a modernized classical K-means algorithm, in which weight coefficients and control pixels are additionally introduced as parameters. It is shown that as a result of using the "controlled cluster analysis" algorithm, the accuracy of esti-mating the size and configuration of the areas of ecological zones increases. The proposed algorithm makes it possible to calculate the total areas of ecological zones of forests more accurately, which can be proposed as a basis for assessing the degree of environmental degradation and the magnitude of environmental damage to forests.