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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Detalhes bibliográficos

Principais autores:	Jie Song, Shengjun Zhang, Xiangxue Kong, Chujiang Liao, Hang Li, Defu Che
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Taylor & Francis Group 2025-12-01
coleção:	Geocarto International
Assuntos:	Water extraction flood mapping deep learning SAR multimodal feature fusion
Acesso em linha:	https://www.tandfonline.com/doi/10.1080/10106049.2025.2596248
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