Abstract
Abstract. 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.