Scientific publications

Remote sensing technologies open up wide opportunities for research in various fields, allowing for a rapid study of vast territories. The use of remote sensing data is being actively introduced into territorial management systems, helping preserve the integrity of natural ecosystems. Mires are particularly challenging to analyze, as they are characterized by high spatial heterogeneity, temporal dynamism, and similarity of spectral characteristics with other types of vegetation. This article examines the potential of using automated interpretation of remote sensing data to delineate wetland areas. We undertook to develop and describe an optimal algorithm for automated recognition of large mire landscapes and reliable delineation of these natural features. The relevance of this study stems from the need to develop effective algorithms for rapidly differentiating mires out of large areas, and thus save on labor-intensive fieldwork. It is important to note that the scientific literature still lacks universal methods for interpreting large areas of mire landscapes. The study was conducted in the eastern part of the Vsevolozhsk District of the Leningrad Region – an area
characterized by active economic development, including not only the expansion of urban and rural communities, but also the construction of ring roads and railways. The selected area is of particular interest due to the diversity of its mire ecosystems and unique natural features, which include more than 40 protected areas, a ramified transportation network, and cultural heritage sites. The authors have developed an algorithm for identifying the boundaries of wetland systems encompassing several mire areas. The theoretical significance of this study lies in exploring the potential of automated classification methods and satellite imagery for studying large areas of mire landscapes. Its practical value consists in conducting a comparative analysis of automated classification methods, which could be useful for subsequent ecological, biogeographical, and wetland studies and for simplifying the process of creating geobotanical maps.