Rare-metal pegmatite–greisen systems are commonly small, structurally controlled, and difficult to delineate using conventional mapping alone. This study proposes a multiscale remote-sensing workflow for prospecting Li–Nb–Ta–Cs mineralisation in the Kalba–Narym rare-metal belt (East Kazakhstan) by integrating Sentinel-2 multispectral imagery, UAV-derived centimeter-scale orthomosaics, structural (lineament) analysis, and field-based mineralogical–geochemical validation. Sentinel-2 responses were first calibrated using known occurrences to derive alteration proxies related to greisenisation, silicification, Na-metasomatism, and oxidation. These proxies were combined into an Integrated Hydrothermal Alteration Index (IHAI) to highlight areas where multiple alteration processes overlap. Lineament mapping from Sentinel-2 and DEM products indicates dominant NW–SE and NE–SW structural trends, zones of elevated lineament density and intersection systematically coincide with high IHAI values. UAV orthomosaics refine satellite-scale anomalies by resolving quartz-vein networks, fracture corridors, and surface-alteration textures that are not detectable at 10–20 m resolution. Mineralogical and geochemical data confirm that high-IHAI targets correspond to albitised pegmatites and greisenised rocks enriched in Li, Nb, Ta, and Cs. The results demonstrate that combining freely available Sentinel-2 data with UAV observations and targeted ground validation provides a cost-effective and transferable framework for reducing false positives and prioritising exploration targets in structurally complex granitoid terranes.

This paper studies the influence of meteorological factors on avalanche occurrence in East Kazakhstan using modern data analysis methods. A dataset of 111 avalanche events in nine avalanche-prone areas of the region, recorded between 2012 and 2023, was compiled. Primary data on avalanche dates were obtained from the Department of Emergency Situations of East Kazakhstan Region (DES EKR), and meteorological data were sourced from the Kazhydromet website. Descriptive statistics, correlation analysis, principal component analysis (PCA), as well as K-means clustering and DBSCAN algorithms, were used for the analysis. During the analysis of meteorological conditions preceding avalanches at nine avalanche-prone areas in Eastern Kazakhstan, using PCA (Principal Component Analysis), the main weather factors affecting avalanche formation were determined. Clustering of 111 avalanches using the K-Means method allowed the identification of four scenario types: gradual snow accumulation without wind (33 cases), upper layer thawing due to warming (34), high snow cover (28), and storm impact (16). The DBSCAN method revealed two anomalous cases related to extreme snow depth. Correlation analysis revealed significant relationships between avalanches and meteorological parameters such as air temperature, snow cover depth, wind speed and direction, precipitation, and relative humidity. Correlation analysis revealed both negative and positive relationships between meteorological parameters. Principal component analysis identified the most significant variables affecting avalanche activity, with temperature, snow cover height, and wind making the greatest contributions. Cluster analysis demonstrated that avalanches could occur under different combinations of weather conditions within the same areas, confirming the complex nature of avalanche-forming processes. The results emphasize the need for an integrated approach to avalanche forecasting that accounts for the multi-parametric interactions of meteorological factors, and may contribute to the improvement of avalanche risk monitoring and mitigation systems in mountain regions.

The article addresses the pressing issue of water security, which has emerged as a significant global risk in the 21st century. With the annual increase in water resource demands due to population growth and socio-economic factors, Kazakhstan faces unique challenges related to its geographical position and reliance on transboundary rivers. Eastern Kazakhstan is one of the most water-rich regions in the country, featuring the Irtysh River and numerous tributaries. Meltwater annually causes flooding, resulting in significant damage, while its potential remains underutilized in agriculture. n this study, remote sensing technologies were applied through the processing of satellite imagery from NOAA, TERRA, AQUA, Sentinel-1, and Sentinel-2 for the period 2017–2022 to analyze flood events. A digital terrain model (DTM) was constructed to delineate watershed areas. The results indicate that floods are primarily associated with spring snowmelt and predominantly affect regions such as Abai, Ayagoz, and Zaysan, with a potential inundation area of up to 468,9 km². To address these issues, the article proposes the creation of reserve reservoirs to manage surface runoff and drainage from temporarily flooded areas. Research has identified 12 potential sites for the creation of reservoirs, which will not only minimise flood damage but also make effective use of meltwater. This strategy not only reduces flood risks but also improves the availability of water resources for agriculture during dry periods. The results show that the use of modern technologies can significantly improve water resource forecasting and management, which in turn contributes to food security and sustainable natural resource use in a changing climate.

Industrial facilities regularly require reconstruction or replacement of individual elements. To solve such problems, design organisations are increasingly using digital 3D models, which are created using data from terrestrial laser scanning, among other sources. s an example, several facilities of “Kazzinc” LLP were examined, covering the entire workflow from field surveys to the final results. During laser scanning, the average error in point cloud alignment was no more than 7 mm, which meets the requirements for data accuracy between stations of no more than 15 mm.The article highlights the advantages of terrestrial laser scanning (TLS), such as high measurement accuracy and reduced human error. The analysis of deviations from design specifications revealed potential conflicts, which helps to prevent delays and additional costs.Despite these achievements, the main limiting factor remains the lack of regulatory and technical documentation in Kazakhstan governing the use of TLS. In conclusion, it is emphasized that the further development and standardization of TLS methods could significantly enhance the quality and safety of engineering works.