Overcoming the Uncertainty Challenges in Flood Rapid Mapping with Multi-Source Optical Data
Author:
Affiliation:
1. Wuhan University,State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing,Wuhan,China,430079
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641074.pdf?arnumber=10641074
Reference19 articles.
1. Analysis of the flood extent extraction model and the natural flood influencing factors: A GIS-based and remote sensing analysis
2. A Novel Fully Automated Mapping of the Flood Extent on SAR Images Using a Supervised Classifier
3. Esa worldcover: Global land cover mapping at 10 m resolution for 2020 based on sentinel-1 and 2 data;Van De Kerchove
4. Very deep convolutional networks for large-scale image recognition;Simonyan,2014
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