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Application of a deep learning framework integrating SAR imagery and terrain slope to flood mapping

Deep learning and remote sensing are critical to flood mapping, with synthetic aperture radar (SAR) offering a weather-independent data source. To improve segmentation accuracy, we designed a GSConv Block and introduced LSK Attention for low-level feature extraction, forming a lightweight network, G...

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Main Authors: Jie Song, Shengjun Zhang, Xiangxue Kong, Chujiang Liao, Hang Li, Defu Che
Format: Artigo
Language:Inglês
Published: Taylor & Francis Group 2025-12-01
Series:Geocarto International
Subjects:
Water extraction
flood mapping
deep learning
SAR
multimodal feature fusion
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2025.2596248
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