Under conditions of excessive anthropogenic pressure on the environment special attention is paid to the ecological state of the soil in Kazakhstan. The quality of soil is the basis for production of environmentally friendly food products, which also provides a more complete transition to the organic use of land resources. The main sources of pollution are mining and metallurgical enterprises that pollute the environment with heavy metals and their compounds. In a light of the current requirements on sustainable development and transition to a circular economy, it’s necessary to create new models of "intelligent" agriculture, based on the use of automated management technologies, ecosystem modeling. The paper substantiates a method to the environmental assessment of agricultural land in industrial cities based on geoinformation modeling processes of the distribution pollutants in the urban environment. The proposed approach will provide a detailed and objective assessment of the environmental situation and will be the basis for the development of various recommendations for protection and rational use of land, including the development of a number of measures to clean up soil and reduce content of pollutants in soil, plants through introduction of a phytoremeditation system, use of natural bentonite clays and other minerals.

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 explores the potential of remote sensing (RS) applications for identifying patterns of rare metal mineralization in the studied area of Eastern Kazakhstan. An analysis of the technical parameters related to RS data is conducted to highlight the structural and lithological features, which allows for a deeper understanding of the geological environment and the region's potential resources. The research is based on multispectral satellite data obtained within potentially promising magmatogenic ore systems. The authors emphasize the identification of areas with a high probability of discovering rare metal mineralization, which can play a crucial role in the exploration and development of deposits. A key element of the study is the analysis of spectral characteristics of rare metal pegmatites and their constituent minerals, enabling the establishment of their unique signatures in the spectral data. The article also discusses the methods for processing and interpreting multispectral images, which are essential for accurately identifying minerals and assessing their distribution. Modern machine learning techniques are applied in the research, significantly increasing the efficiency of data analysis and allowing for the automation of mineral identification and classification processes. As a result, meaningful conclusions are drawn about the region's potential for rare metal extraction, opening new prospects for further research and practical applications in geological exploration.

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.

Мақала гетерогенді геологиялық графикалық материалдарды өңдеу және соның негізінде географиялық ақпараттық жүйeлерінің (ГАЖ) мәліметтер базасын құрудың техникалық және технологиялық шешімдері қарастырылады. Нысан ретінде Шығыс Қазақстанда орналасқан, Қалба-Нарым металлогенді зонасы және оның құрылымдық бөлігі – Асубулақ кен өрісі алынған. ГАЖ мәліметтер базасын құру барысында құрамы және масштабы бойынша түрлі геологиялық деректер қолданылды, атап айтқанда: геологиялық, геофизикалық (гравиметриялық және магниттік аномалия карталары), геохимиялық және пайдалы қазбалар карталары. Дәлдігі мен ақпарат толықтығын жақсарту үшін векторизацияланған сандық карталар қашықтықтан зондтау мәліметтерімен толықтырылған. Біріккен ГАЖ жүйесі арқылы геологиялық сипаттамаларға кешенді кеңістіктік талдау жүргізуге мүмкіндік алынды This article discusses technical and technological solutions for processing heterogeneous Geological graphic materials and creating databases of geographic information systems (GIS) based on them. As a sample, the Kalba-Narym Metallogenic zone and its structural part – the Asubulak ore field, located on the territory of Eastern Kazakhstan, were taken. In the process of creating the GIS database, various geological data were used in terms of composition and scale, in particular: geological, geophysical (gravimetric and magnetic anomaly maps), geochemical and mineral maps. Vectorized digital maps are supplemented with remote sensing data to improve accuracy and informativeness. Through the combined GIS system, we have the opportunity to conduct a comprehensive spatial analysis of geological characteristics В статье рассматриваются технические и технологические решения по обработке неоднородных геологических графических материалов и созданию на их основе базы данных географических информационных систем (ГИС). В качестве объекта взята Калба-Нарымская металлогеническая зона и ее структурная часть – Асубулакское рудное поле, расположенное на территории Восточного Казахстана. При создании базы данных ГИС использовались различные геологические данные по составу и масштабу, а именно: геологические, геофизические (гравиметрические и магнитные карты аномалий), геохимические и карты полезных ископаемых. Векторизованные цифровые карты дополнены данными дистанционного зондирования для улучшения точности и информативности. Благодаря объединенной системе ГИС получена возможность проводить комплексный пространственный анализ геологических характеристик