Mapping Outburst Floods Using a Collaborative Learning Method Based on Temporally Dense Optical and SAR Data: A Case Study with the Baige Landslide Dam on the Jinsha River, Tibet

Mapping Outburst Floods Using a Collaborative Learning Method Based on Temporally Dense Optical and SAR Data: A Case Study with the Baige Landslide Dam on the Jinsha River, Tibet

Outburst floods resulting from giant landslide dams can cause devastating damage to hundreds or thousands of kilometres of a river. Accurate and timely delineation of flood inundated areas is essential for disaster assessment and mitigation. There have been significant advances in flood mapping usin...

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Bibliographic Details
Main Authors: Zhongkang Yang, Jinbing Wei, Jianhui Deng, Yunjian Gao, Siyuan Zhao, Zhiliang He
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
outburst flood
Sentinel-1
Sentinel-2
threshold
false color composite images
ground roughness
Online Access:https://www.mdpi.com/2072-4292/13/11/2205

Internet

https://www.mdpi.com/2072-4292/13/11/2205

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