Hybrid ViT-UNet Framework for Accurate River Segmentation and Buffer Zone Mapping in High-Resolution Satellite Imagery
This paper introduces a deep learning model for effective segmentation of rivers, lakes, and reservoirs from high-resolution Gaofen-2 satellite images, and demonstrates the potential of transformer-based segmentation models for remote sensing achieved accuracy of 98% for environmental risk management and decision support in disaster-prone areas.