A decoding technique was applied using geoinformation systems and technologies based on remote sensing data in a study of forest vegetation with the aim of developing a more efficient method for deciphering forest inventory and obtaining maps of forestation of reference forest areas. The signs of interpretation for the analysis of the initial data, the distribution of objects into groups, the study of the features of forest taxation interpretation, the classification of groups by forest taxation features, the fixation of studies in the software environment and the subsequent display of the results are used. With the help of interpretation skills, data analysis was performed, which resulted in the basic classification of objects into groups according to more general characteristics, and then the thematic classification of the selected groups of forest communities. Since the subject of the study is the application of geoinformation systems and technologies in the field of forest-affected decoding, the fulfillment of all tasks was fixed in the software environment. The authors determine that one of the main stages of forest-affected decoding is the determination of the wood composition of forests. In order to determine the wood composition, it is necessary to identify certain characteristics and differences of each tree species from each other. In the pictures we see only the crowns of trees, so all the signs of recognition are determined by them. The key goal of forest-space decoding of space is established - the recognition of what species make up certain forest areas, as well as the determination of quantitative taxation indicators. At present, it is possible to obtain all the necessary remote sensing data of the Earth in high resolution, which will help to study the forest almost to the detailed level.
Forest taxation research, geoinformation technologies, space images, recognition of tree species
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