Enhancing satellite image segmentation for land use and land cover analysis using attention-based deep learning approach

Key Points

• Segmentation results improved significantly, enhancing the clarity of land use classifications.
• Accuracy rates reached 92% for land cover types, showcasing the method's effectiveness.
• Application of an attention-based deep learning approach optimized image processing techniques.
• The findings highlight the need for advanced methods in remote sensing and land management.