Investigation of the topological structure of images using augmentation

№1 (2025) Eremeev S.V., Abakumov A.V., Pankratov D.A., Khavronin B.A. УДК 004.9 https://doi.org/10.47148/1609-364X-2025-1-72-78 Key words: image augmentation; satellite images; topological structure of images; structural similarity indices Section: Artifical intelligence in applied fields of knowledge

Geoecological assessment of oil-contaminated landscapes of the Republic of Bashkortostan

№4 (2024) Nafikova E.V., Shaniyazova A.F., Aleksandrov D.V., Khuzhina R.R. УДК 553.982.2 https://doi.org/10.47148/1609-364X-2024-4-57-69 Key words: geoecological assessment; oil spill; petroleum products; statistical analysis; emergency situations; spill causes; prevention measures; impact on ecosystems; administrative regions; soil cover; landscape cover Section: Geoecology

Determination of channel curvature in the map forecast model of river meandering

№1 (2024) I.K. Lurie УДК 556.537 https://doi.org/10.47148/1609-364X-2024-1-28-34 Key words: channel, river, meandering, river bed channel displacement, curvature, center of curvature, approximation, spline, least squares method, digital coordinate transformation, algorithm, hydrological monitoring Section: Modeling geo objects and geo-processes

Geoinformation model of river meandering for predictive mapping

№2 (2023) https://doi.org/10.47148/1609-364X-2023-2-9-16 Lurie I.K., Lurie M.V. Key words: predictive mapping, riverbed, meandering, riverbed deformation, spline, curvature, center of curvature, displacement, digital transformation, algorithm, monitoring Section: Application of GIS technologies

Application of the permutation method to the assessment of predictive ability of the models of spatial distribution of copper and iron concentrations in the topsoil

№2 (2022) Sergeev A.P., Butorova A.S., Shichkin A.V., Buevich A.G., Baglaeva E.M., Subbotina I.E. УДК 504.064.2.001.18 https://doi.org/10.47148/1609-364X-2022-2-42-53 Key words: permutation method, randomization, predicted values, observed values, spatial distribution, predictive ability assessment, artificial neural networks Section: Modeling geo objects and geo-processes