Nurakynov S 1
1. Predicting and detecting fires on multispectral images using machine learning methods
2. A Study on Deep Learning-Based Predictive Modeling of Vegetation Dynamics in Kazakhstan through the Integration of CNNs, RNNs, and Satellite Imagery for Ecological Monitoring
3. Advanced Spaceborne InSAR for monitoring tectonic and anthropogenic ground deformation in the seismically sensitive Almaty region, Kazakhstan
4. Quantitative assessment of urban surface deformation risks from tectonic and seismic activities using multitemporal microwave satellite remote sensing: a case study of Almaty city and its surroundings in Kazakhstan
5. Mapping fire hazard potential in Kazakhstan: a machine learning and remote sensing perspective
6. Dependence of Avalanche Risk on Slope Insolation Level and Albedo
7. Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems
8. Enhancing Environmental Sensitivity and Vulnerability Assessments for Oil Spill Responses in the Caspian Sea
9. Predictive System for Road Condition Monitoring based on Open Climate and Remote Sensing Data - A Case Study with Mountain Roads
10. The First Inventory of Rock Glaciers in the Zhetysu Alatau: The Aksu and Lepsy River Basins
11. Application of Artificial Intelligence in Landslide Susceptibility Assessment: Review of Recent Progress
12. Occurrence and Characteristics of Rock Glaciers in Western Tien Shan
13. Accelerated Glacier Area Loss in the Zhetysu (Dzhungar) Alatau Range (Tien Shan) for the Period of 1956–2016
14. Advancements in Remote Sensing for Monitoring and Risk Assessment of Glacial Lake Outburst Floods
15. Application of Artificial Intelligence in Glacier Studies: A State-of-the-Art Review
16. Application of Finite Element Method for Solving Seismoacoustic Modeling Problems in Poroelastic Composite Media
17. Predicting the Likelihood of an Earthquake by Leveraging Volumetric Statistical Data Through Machine Learning Techniques
18. Satellite based deep learning approaches for detecting environmental disasters across Kazakhstan
19. A PLL-Based Doppler Method Using an SDR-Receiver for Investigation of Seismogenic and Man-Made Disturbances in the Ionosphere
20. Disturbances of Doppler Frequency Shift of Ionospheric Signal and of Telluric Current Caused by Atmospheric Waves from Explosive Eruption of Hunga Tonga Volcano on January 15, 2022
21. Investigation of the Pre- and Co-Seismic Ionospheric Effects from the 6 February 2023 M7.8 Turkey Earthquake by a Doppler Ionosonde
22. Monitoring of Gamma Radiation Prior to Earthquakes in a Study of Lithosphere-Atmosphere-Ionosphere Coupling in Northern Tien Shan
23. Seismogenic Effects in Variation of the ULF/VLF Emission in a Complex Study of the Lithosphere–Ionosphere Coupling Before an M6.1 Earthquake in the Region of Northern Tien Shan
24. The Time Delays in Reaction of the Ionosphere and the Earth’s Magnetic Field to the Solar Flares on 8 May and Geomagnetic Superstorm on 10 May 2024
25. Combination of Soviet-Era Surface Gravity and Modern Satellite Data for Geoid Model Computation: A Case Study for Kazakhstan
26. Evaluation of a Soviet-Era Gravimetric Survey Using Absolute Gravity Measurements and Global Gravity Models: Toward the First National Geoid of Kazakhstan
27. Temporal variations of geoid heights over Kazakhstan from GRACE–FO data and their relation with hydrological changes in the Caspian Sea and seismic activity
28. Hybrid Geoid Modelling with AI Enhancements: A Case Study for Almaty, Kazakhstan
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