Technology of improving the land use data accuracy for geospatial modeling tasks

• Date: 2026
• Main Authors: Okhariev, Viacheslav, Pidsadnii, Serhii
• Format: Article
• Language: Ukrainian
• Published: Kyiv National University of Construction and Architecture 2026
• Subjects: geospatial modeling; land use data; machine learning
• Online Access: https://es-journal.in.ua/article/view/364955
• Journal Title: Environmental safety and natural resources

The aim of the research is increasing the accuracy of land cover classification (LULC) based on Dynamic World (DW) data for the controlled territory of Ukraine. One of the key problems of such data is the regional specificity of the land use regime, which reduces the reliability of the global averag...