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Information × Registration Number 0126U001152, R & D request Title Detection of mineral deposits on the Moon by new methods of observational astronomy based on machine learning Head Vadym H. Kaidash, Кандидат фізико-математичних наук Registration Date 30-01-2026 Organization Karazin University popup.description1 The overall goal of the project is to develop and improve effective observational methods and technologies for predicting the chemical and mineralogical composition of the Moon's surface based on the joint analysis of data from various space instruments obtained with high spectral and spatial resolution, machine learning methods. The problem of detecting promising places of mineral deposits on the Moon and determining their content in the lunar soil based on the development and improvement of observational astronomy methods, including telescopic and space observation technologies, is solved in three directions: (1) Combining the spectral mixing model developed by the authors with machine learning (ML) methods for mapping the composition of lunar regolith. Joint use of observational data from various space instruments obtained with high spectral and spatial resolution to determine local anomalies in the composition and structure of the surface using artificial neural networks. (2) Photometric and geometric correction of photometry and spectrometry data of the Moon's surface with spatial resolution at the level of initial data using observational methods developed by the authors of the project, which are based on stereophotogrammetry and multiphase photoclinometry and constitute a complex of programs for processing space images. (3) Mapping and studying the distribution of individual mineralogical components and helium-3 from orbital spectrometer data. Estimation of volatile components (in particular, hydrogen compounds) using infrared spectral data and a novel analytical thermal model for calculating the emissivity of the lunar surface to account for the anisothermal effect. popup.nrat_date 2026-01-30 Close