Modeling the heavy metals spatial distribution structure in urban soils based on the thematic processing remote sensing data results

№1 (2026) Dobrynin D.V., Sukhova O.V. УДК 504.064 https://doi.org/10.47148/1609-364X-2026-1-56-71 Key words: Geographic Information Systems; Remote Sensing Data; Heavy Metals; Urban Landscapes; Spatial Distribution Modeling. Section: Geoecology

Individual and pair representativeness of sampling points selection in interpolation tasks of the heavy metals distribution in the topsoil

№3 (2023) УДК 504.064.2.001.18 https://doi.org/10.47148/1609-364X-2023-3-63-70 Baglaeva E.M., Sergeev A.P., Shichkin A.V., Buevich A.G., Butorova A.S. Key words: representativeness of points, sampling, heavy metals, artificial neural networks, choice of training subset Section: Geoecology

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

GEW personal account: software and technological environment for storing, processing and providing results of regional geological-geophysical and geological surveying works on regional study of subsoil and reproduction of mineral resource base of hydrocarbon raw materials

№3 (2021) УДК 553.98+004.9 DOI: 10.47148/1609-364X-2021-3-55-62 A.A. Koneva, K.A. Koneva, K.N. Markov, A.A. Suleimanov Key words: information system; GEW personal account; Unified Bank of Geological and Geophysical Information of VNIGNI; MGS-Framework; software and technological complex for subsoil geological study and … Continue reading →

Surface interpolation of heavy metal contents in the soil by machine learning methods.

№1 (2019) Buevich A.G., Moskaleva A.S.,Kosachenko A.I., Shichkin A.V., Sergeev A.P. Section: Modeling geo objects and geo-processes Keywords: artificial neural networks, random forest, random perceptron forest, interpolation, heavy metals, soil.

№1 (2026)

Geoinformation system «Forest Fires – MPI SB RAS (Yakutia)»Vasiliev М.S. GIS and PostgreSQL: Modern Technologies for Monitoring Karst HazardsKitaeva М.A., Drobinina E.V., Romanova E.R.Application of GIS-technologies and digital photogrammetry for studying the structure and development of Сape Tyteri on Lake BaikalLunina M.A., Lunina … Continue reading →

On the use of large language models in applied tasks of the oil and gas industry

№4 (2025) Prozorova G.V., Senkevich L.B. УДК 004.9, 004.8, 553.98 https://doi.org/10.47148/1609-364X-2025-4-103-112 Key words: Large Language Model; LLM; oil and gas industry; artificial intelligence Section: Artifical intelligence in applied fields of knowledge

Interaction models of cartographic and geoinformation support

№4 (2025) Loginov D.S. УДК 528.91 + 528.942 https://doi.org/10.47148/1609-364X-2025-4-90-102 Key words: bibliographic analysis; geoinformation support; dissertation research; cartographic support; natural relationship models; resource management; subsoil management Section: Personnel training

Forecasting water levels based on time series of ground-based data and satellite collections using regression models

№4 (2025) Chuldum A.F., Chupikova S.A. УДК 519.6:528.9:551.435.16 https://doi.org/10.47148/1609-364X-2025-4-81-89 Key words: hydrological forecasts; time series; satellite data; regression methods; forecasts of water levels Section: Practical application

Development of geoinformation technology for comprehensive assessment of environmental risk to public health on the example of the territory of the city of Dubna

№4 (2025) Cheremisina E.N., Lyubimova A.V., Dobrynin D.V., Goryunova E.A., Kamanina I.Z. УДК 004.9https://doi.org/10.47148/1609-364X-2025-4-12-22 Key words: environmental risk; geoinformation model; spatial data; integrated analysis; GIS INTEGRO Section: Application of GIS technologies

Geoinformatika

Journal of geoinformation technologies in geology and geoecology

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