The SCO-Flooddam Digital Twin Project: A Pre-Operational Demonstrator for Flood Detection, Mapping, Prediction and Risk Impact Assessment-Reference-Cited by-同舟云学术

The SCO-Flooddam Digital Twin Project: A Pre-Operational Demonstrator for Flood Detection, Mapping, Prediction and Risk Impact Assessment

Published:2024-07-07 Issue: Volume: Page:2009-2012
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Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Suquet R. Rodriguez¹,Nguyen T.H.²,Ricci S.²,Piacentini A.²,Bonassies Q.²,Sadki M.²,Fatras C.³,Lavergne E.³,Gaudissart V.⁴,Guzzonato E.⁴,Prugniaux M.⁴,Froidevaux A.⁵,Aouassar O.⁵,Valladeau G.⁶,Poisson JC.⁶,Huang T.⁷,Bretar F.¹

Affiliation:

1. Centre National d’Études Spatiales (CNES),Toulouse Cedex 9,France,31401

2. Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CECI, UMR5318 CNRS/CERFAC S),Toulouse Cedex 1,France,31057

3. Collecte Localisation Satellites (CLS) Group,Ramonville-Saint-Agne,France,31520

4. CS Group,Toulouse,France,31500

5. QuantCube Technology,Paris,France,75002

6. VorteX.io,Toulouse,France,31400

7. California Institute of Technology,Jet Propulsion Laboratory (JPL),Pasadena,California,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640907.pdf?arnumber=10640907

Reference11 articles.

1. The Sco-Flooddam Project: New Observing Strategies for Flood Detection, Alert and Rapid Mapping

2. The SCO-Flooddam Project: Towards A Digital Twin for Flood Detection, Prediction and Flood Risk Assessments

3. An Earth System Digital Twin for Flood Prediction and Analysis

4. Distributed Machine Learning and Data Fusion for Flood Detection and Monitoring;Huang

5. High-resolution mapping of global surface water and its long-term changes