Recognition of urban water bodies using deep learning with multi-source and multi-temporal high spatial resolution remote sensing imagery

  Data from High Spatial Resolution Remote Sensing Imagery (HSRRSI) provides detailed information required for the recognition of surface water bodies, including the texture, geometric structure and spatial distribution of these liquid masses. The comprehensive information gathered means that the internal components of surface water bodies can be represented, and the relationship between adjacent objects are better reflected. In the […]

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