Abstract

In the context of urbanization processes and the territorial expansion of urban areas, the term "urban sprawl" or "urban sprawl" is used to describe the "phenomenon of urban sprawl. This is a complex geographical process, which can be investigated on the basis of modern remote sensing data, including the use of multispectral satellite images of the Landsat project. The study actualized the process of processing and analysis of images using modern GIS complexes. As a result, the methodology of interpretation, mapping and calculation of changes in the dynamics of urbanized area growth for St. Petersburg was presented and tested. Each image was classified using machine learning by height standards. A class of urbanized areas was separately identified for each year of analysis. As part of this work, a map of the dynamics of urbanized territories over the study period was constructed, and the growth of the area of territories over the analysis period was quantitatively calculated. As a result, Landsat project space images, obtained due to the capabilities of the USGS database, turned out to be quite effective for detecting urban areas, water bodies, unused land and vegetation cover. Testing of the method on the example of St-Petersburg allowed seeing the results of expanding the built-up territory at the expense of peripheral (suburban) zones, including the effect of suburbanization. Over 25 years, urbanized areas have expanded due to the construction of infrastructure road facilities and housing construction of both low-rise projects and residential buildings, as well as large residential complexes. Further development of this study will include the Leningrad Oblast contact area as part of the St. Petersburg urban agglomeration.

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