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    RU-Net++: An automatic extraction method for Impervious Surface Area based on neural networks

    RU-Net++: An automatic extraction method for Impervious Surface Area based on neural networks by F. Yu, X. Tu, L. Cai, J. Zhang, Z. Wang

    Published 2025-08-01

    Impervious Surface Area (ISA) is vital for urban planning, environmental monitoring, and water management. Traditional remote sensing methods struggle with complex urban landscapes, leading to accuracy limitations. To address this, we propose RU-Net++, a deep learning-based ISA extraction model inte...

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