Geoinformation analysis of forest types of geosystems using spectral index estimation
Abstract and keywords
Abstract:
This article presents the results of a geoinformation analysis of forest geosystems of mixed forests in the Zubovo-Polyansky District of the Republic of Mordovia on aquiglacial plains using spectral indices calculated from Sentinel-2 satellite imagery for 2020–2025. The aim of the study was to identify the dynamics of vegetation, soil, and water cover, as well as urbanized areas, to assess the impact of natural and anthropogenic factors. The methodological framework included the selection of initial remote sensing data, its preprocessing, the calculation of indices for the main components of the geosystems, and the classification and verification of the results using cartographic materials and in situ observations. For vegetation, the EVI2, CCCI, and PSRI indices were used to estimate the total biomass, chlorophyll content, and aging processes. It was established that over a five-year period, the area of areas with maximum vegetation indices decreased and the proportion of zones with average values increased. This is associated with clear-cutting, quarry expansion, and road network development, while abandoned agricultural lands were being reforested. For soil cover, the BSI, SCI, and NDSI indices were used, revealing an increase in the area of bare surfaces within forested areas and a trend toward decreasing humus content with increasing salinity. For water bodies, the AWEI and NDTI indices were used, demonstrating the stability of contours and constant turbidity. Urbanized areas were assessed using the BAEI index, confirming local changes and the construction of a new highway. A conclusion was reached regarding the declining bioproductivity of forest geosystems and partial degradation of soil cover while maintaining the stability of water bodies.

Keywords:
geoinformation analysis, remote sensing of the Earth, soil degradation, vegetation cover, hydrological monitoring, urban areas, nature management
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