Enhancement of Detecting Permanent Water and Temporary Water in Flood Disasters by Fusing Sentinel-1 and Sentinel-2 Imagery Using Deep Learning Algorithms: Demonstration of Sen1Floods11 Benchmark Datasets

Identifying permanent water and temporary water in flood disasters efficiently has mainly relied on change detection method from multi-temporal remote sensing imageries, but estimating the water type in flood disaster events from only post-flood remote sensing imageries still remains challenging. Re...

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Principais autores:	Yanbing Bai, Wenqi Wu, Zhengxin Yang, Jinze Yu, Bo Zhao, Xing Liu, Hanfang Yang, Erick Mas, Shunichi Koshimura
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2021-06-01
Colecção:	Remote Sensing
Assuntos:	deep learning Sen1Floods11 datasets multi-source data fusion Sentinel-1 Sentinel-2 permanent water
Acesso em linha:	https://www.mdpi.com/2072-4292/13/11/2220
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