Exploring the Potential of Multi-Sensor and Multi-Scale Remotely Sensed Data Integration to Improve Flood Monitoring
Author:
Affiliation:
1. University of Bari Aldo Moro,Dept. of Earth and Geoenvironmental Sciences (DISTGEO),Bari,Italy,70125
2. National Research Council of Italy (CNR),Institute for the Electromagnetic Sensing of the Environment (IREA),Bari,Italy,70126
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640962.pdf?arnumber=10640962
Reference6 articles.
1. Satellite-Based Flood Mapping through Bayesian Inference from a Sentinel-1 SAR Datacube
2. A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data
3. Improving Flood Monitoring Through Advanced Modeling of Sentinel-1 Multi-Temporal Stacks
4. High-Resolution Flood Monitoring Based on Advanced Statistical Modeling of Sentinel-1 Multi-Temporal Stacks
5. Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters
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