ISPOL'ZOVANIE MATERIALOV KOSMICHESKOY S'EMKI PRI OCENKE PRIRODNO-RESURSNOGO POTENCIALA URBANIZIROVANNYH TERRITORIY
Abstract and keywords
Abstract (English):
This article examines the issues of improving the methodology of assessing the natural resource potential of urban areas using space imagery. The subject of the study is based on a visual and automatic decryption and techniques of space image classification. With the help of space imagery materials, the dynamics of areas of forest tracts, damaged trees, residential areas, arable lands of various urban areas, water bodies have been revealed. The main parameters of modern satellites are presented. An algorithm for assessing the effectiveness of the use of remote sensing materials for solving various land monitoring problems is proposed. With the help of automated interpretation, the authors distinguish four classes of quality of woody vegetation in urbanized areas. The authors evaluate the advantages and disadvantages of methods for deciphering of forest felling with automated and visual recognition of felling. The authors identify areas of flooding of specific urbanized areas.

Keywords:
automatic decryption, natural resource potential, space imagery, state of land, visual decryption
Text
This article examines the issues of improving the methodology of assessing the natural resource potential of urban areas using space imagery. The subject of the study is based on a visual and automatic decryption and techniques of space image classification. With the help of space imagery materials, the dynamics of areas of forest tracts, damaged trees, residential areas, arable lands of various urban areas, water bodies have been revealed. The main parameters of modern satellites are presented. An algorithm for assessing the effectiveness of the use of remote sensing materials for solving various land monitoring problems is proposed. With the help of automated interpretation, the authors distinguish four classes of quality of woody vegetation in urbanized areas. The authors evaluate the advantages and disadvantages of methods for deciphering of forest felling with automated and visual recognition of felling. The authors identify areas of flooding of specific urbanized areas.
References

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