Abstract
This project develops a robust land cover classification system using CNNs for Sentinel-2 imagery, crucial for detecting land use changes and enhancing mapping. Leveraging Copernicus data ensures accessibility and integration into broader Earth observation initiatives, benefiting various fields. Keywords— Sentinel-2 imagery, Convolutional Neural Networks (CNNs), Copernicus program, remote sensing, land use changes, environmental studies, urban planning.
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