Browsing by Author "Kavats, Yurii V."

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    Machine Learning-Based Monitoring of War-Damaged Water Bodies in Ukraine Using Satellite Images
    (CEUR-WS Team, Aachen, Germany, 2024) Sergieieva, K.; Kavats, Olena O.; Vasyliev, Volodymyr; Kavats, Yurii V.; Kovrov, Oleksandr
    ENG: Water resources are Ukraine's strategic environmental asset. As a result of the destruction caused by the Russo-Ukrainian War, critical water infrastructure has been severely damaged. This makes it essential to effectively manage and conserve water resources in the face of increasing anthropogenic impact. The use of machine learning methods to monitor water bodies' conditions based on optical and Synthetic Aperture Radar (SAR) satellite images allows for automating analysis processes and providing more accurate and timely results, which is important for making reasonable management decisions. In this study, information tools for mapping and assessing the dynamics of surface water body changes were developed based on Sentinel-1 and Sentinel-2 data using a convolutional neural network. They were used for the mapping of surface water bodies in the Lower Dnipro sub-basin affected by the destruction of the Kakhovka Hydropower Plant dam. To improve the result of satellite image mixed pixels classification in shallow areas of swampy water bodies at the bottom of the destroyed Kakhovka Reservoir, it is proposed to use a block data model and a probabilistic approach to assess the presence of "water" and "ground" class objects in the images, which allows to achieve mapping accuracy of up to 96%.