A Novel Flood Monitoring Method Using Temporal Information and Statistical Characteristics in SAR Images
Author:
Affiliation:
1. China University of Mining and Technology,School of Environment Science and Spatial Informatics,Xuzhou,China
2. Hebei University of Engineering,School of Mining and Geomatics Engineering,Handan,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10642431.pdf?arnumber=10642431
Reference6 articles.
1. Progress, Challenge and Prospect for Remote Sensing Monitoring of Flood and Drought Disasters in China
2. Monitoring the tropical cyclone ‘Yass’ and ‘Amphan’ affected flood inundation using Sentinel-1/2 data and Google Earth Engine
3. An Urban Flooding Index for Unsupervised Inundated Urban Area Detection Using Sentinel-1 Polarimetric SAR Images
4. Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering
5. Enriching stochastic model updating metrics: An efficient Bayesian approach using Bray-Curtis distance and an adaptive binning algorithm
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