Search Results for: alas

Analysis of alas distribution in the Churapcha Ulus (District)

№1 (2025) Torgovkin Ya.I., Shestakova A.A. УДК 528.8, 551.34 https://doi.org/10.47148/1609-364X-2025-1-13-21 Key words: Central Yakutia Lowland; alas; permafrost landscape; terrain type; alas distribution density; thermokarst; spatial analysis Section: Application of GIS technologies

Distribution of alasses in the Lena-Amga interfluve

№2 (2023) https://doi.org/10.47148/1609-364X-2023-2-17-25 Shestakova A.A., Torgovkin Y.I. Key words: alas, permafrost landscape, type of terrain, density of distribution of alas, ice complex, spatial analysis, Lena-Amga interfluve Section: Application of GIS technologies

№1 (2025)

DOI:10.47148/1609-364X-2025-1 A GIS project of the current state of agricultural lands taken out of circulation after the accident at the Chernobyl nuclear power plant in the Bryansk region Titov I.E., Krechetnikov V.V., Shubina O.A., Krechetnikova E.O.Analysis of alas distribution in the Churapcha Ulus (District) Torgovkin … Continue reading →

Review and Analysis of XAI Methods for Addressing Geoecological Zoning and Public Health Prevention Challenges

№4 (2024) Trofimov Yu.V., Averkin A.N., Cheremisina E.N. УДК 0048 https://doi.org/10.47148/1609-364X-2024-4-93-118 Key words: sustainable development; explainable artificial intelligence (XAI); ecological zoning; geographic information systems (GIS); neuro-fuzzy models; disease prevention; environmental risks; decision support systems; healthcare Section: Artifical intelligence in applied … Continue reading →

An overview of Russian geographic information services on environmental issues based on open source software

№4 (2024) Plotnikova A.S., Khamedov V.A., Arkhiptseva E.A., Podolskaia E.S., Narykova A.N., Alekseev A.B. УДК 551.4.08, 550.83.016, 550.343.4https://doi.org/10.47148/1609-364X-2024-4-4-20 Key words: geoservice; interactive maps; open source software; Leaflet; OpenLayers; OpenStreetMap; Mapbox; Google Earth Engine; API Yandex.Map; the system of state environmental … Continue reading →

Obtaining retrospective data of the urbanized landscape condition using computer vision methods on the example of construction works

№2 (2024) Koryukin E.A., Bobakov V.S., Butorovа А.S., Sergeev A.P. УДК 504.064.2.001.18 https://doi.org/10.47148/1609-364X-2024-2-54-63 Keywords: neural network; urbanized environment; geoinformation system; dataset; object class; image segmentation; library; artificial intelligent; object recognition; mask r-cnn. Section: Methodological and technological support for data collection … Continue reading →

№2 (2023)

DOI:10.47148/1609-364X-2023-2 Geoinformation model of river meandering for predictive mappingLurie I.K., Lurie M.V.Distribution of alasses in the Lena-Amga interfluveShestakova A.A., Torgovkin Y.I. Modeling of the field of currents and sea level using the Cardinal software packageIstomin E.P., Petrov Ya.A., Martyn I.A.Calculation of impurity distribution using … Continue reading →