Since Chernozems are among the most fertile soils in the world, the study of their degradation is of great interest. However, the microstructure and composition of the soil organic matter (SOM) in eroded Chernozems have not yet been sufficiently studied. We studied the SOM and aggregate states of eroded Chernozems using the example of two catenas with arable Haplic Chernozems in the Kursk region of Russia. In the plow horizons (the part of the soil most susceptible to water erosion), we determined the mean-weighted aggregate diameter (MWD), structure and water stability coefficients (SC and WS; dry and wet sieving, respectively), soil organic carbon (SOC) content, and SOM composition and content (qualitative and quantitative micromorphological analyses, respectively). It was shown that with an increase in the degree of erosion, the content of SOC decreased significantly, according to both chemical and micromorphological methods of evaluation. No significant relationships were found between the degree of erosion and the indicators of the structure (except for WS, which was significantly lower in non-eroded Chernozem than in slightly and moderately eroded soils). With the increasing degree of erosion, the humus state of these soils deteriorates at the microlevel, the intensity of humification decreases, the depth of the appearance of assimilated biogenic aggregates with finely dispersed calcite in the profile increases, the structure is destroyed, lumpy aggregates form, and the proportion of planar voids increases. The downslope transport of the soil solid phase under the impact of erosion is accompanied by the accumulation of the transformation products of carbohydrates in the Chernozems in the lower part of the catena. In the Chernozems located in the transit position of the slope, the composition of SOM is characterized by the predominance of lipids and nitrogen-containing compounds. Our unique results contribute to a deeper understanding of the formation of structure and water resistance in eroded soils.

One of the current trends in archaeological geoinformatics in Russia is the creation of web mapping portals that integrate spatial and thematic data on the given areas of concentration of archaeological sites. As part of the study of the life support system of the ancient population of the Tura and Pyshma interfl uves (Tyumen region) developed a geoportal on the basis of free and open source soft ware. The server part developed on the basis of GeoServer, provides storage of the information and authorized access to it. Vector data is stored in PostgreSQL database management system using PostGIS add-in. Raster data is stored on the server as GeoTIFF and MrSID fi les. Th e technologies used in the development of the client web-application allow using it in modern web-browsers without installing additional soft ware on the user’s devices. Th e geoportal user interface is an interactive map of spatial data layers as well as map control elements. Th e general control elements include the zoom buttons, the scale setting on the available layer extents, the zoom slider, the scale bar, the geographic coordinates fi eld of the cursor installation, the button enabling the attribute information display mode. Th ematic content of the geoportal includes space images with medium (10 m) and extra high (up to 0.3 m) spatial resolution, AW3D relief model (25 m), topographic maps, UAV images of certain areas (orthophotomaps and DEM), vectorlayers of archaeological sites, hydrography, landscapes restoration, results of archaeological sites borders mapping using GPS-receivers, as well as the results of bathymetry survey. Th e layer of archaeological site (366 objects) contains attributive information including type, period, description, dating. Geoportal is a convenient tool for management and visualization of the accumulated information arrays for specialists without extensive knowledge in cartography and GIS.

This study examines the possibility for detecting bare soil surface (BSS), using remote sensing data and for applying this approach to model texture and total soil carbon in the topsoil. The study area comprises agricultural fields within the North Caucasus Federal Agricultural Research Center in the northeastern spurs of the Stavropol Upland. Landsat 5/8 imagery and spectral indices (NDVI, NBR2, and BSI) were used to classify BSS. Optimal discrimination of BSS from green and non-photosynthetic vegetation was achieved, using a BSI threshold of >0.18 (F1-score = 0.98). Spatial modeling of topsoil properties was conducted by comparing five regression models (Linear Regression, K-Nearest Neighbors, Random Forest, Extreme Gradient Boosting, and Cubist). A linear regression model demonstrated the highest performance; key predictors included the mean and standard deviation of SWIR2. The model exhibits strong predictive capability for sand, silt, clay, and total carbon (adjusted R ² = 0.82, 0.75, 0.78, and 0.74, respectively). The topsoil is characterized by the range of clay content from 5 to 30%, of silt content from 15 to 60%, of sand content from 20 to 80%, and of total carbon from 0.5 to 3%. Predictive maps of texture and total carbon derived from BSS reveal considerable local heterogeneity, with soils consisting of Chernozems and Phaeozems, influenced by parent rock variability. The modeling results highlight the high predictive power of the BSS spectral characteristics, even when used as a single predictor for digital soil mapping.