Flood Mapping Using Sentinel-1 Images and Lightweight U-Nets Trained on Synthesized Events
Author:
Affiliation:
1. IBM Research Brazil, Rio de Janeiro, Brazil
2. IBM Research Europe, Rüschlikon, Switzerland
3. IBM Research Europe, Warrington, U.K.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology
Link
http://xplorestaging.ieee.org/ielx7/8859/10034981/10220434.pdf?arnumber=10220434
Reference13 articles.
1. Google Earth Engine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for Rapid and Large Scale Flood Analysis
2. IBM PAIRS curated big data service for accelerated geospatial data analytics and discovery
3. High-resolution mapping of global surface water and its long-term changes
4. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Int Conf Med Image Comput Comput -Assist Intervent,2015
5. Sentinel-1-Based Water and Flood Mapping: Benchmarking Convolutional Neural Networks Against an Operational Rule-Based Processing Chain
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3. Detection of methane plumes using Sentinel-2 satellite images and deep neural networks trained on synthetically created label data;2023 IEEE International Conference on Big Data (BigData);2023-12-15
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