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Author/Chair
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  • Sagy Cohen

    University of Alabama
Notes
Meeting roles in:
Transferable Flood Inundation Mapping Using Deep Learning Trained on LISFLOOD-FP Outputs and Synthetic Hydrographs
Toward Robust Large-scale Evaluations of Flood Inundation Predictions
Flood Inundation Mapping within Operational Hydrological Forecasting: the July 4 Texas Flooding Case Study
Recent Advances in Remote Sensing and Modeling of Flood Inundation I Oral
A Framework for Large-scale Flood Inundation Mapping and Evaluation over an Extensive Benchmark Database.
Recent Advances in Remote Sensing and Modeling of Flood Inundation II Oral
Sensitivity of Terrain-based Flood Inundation Model (OWP HAND-FIM) Predictions to Channel Geometry: Insights from Bathymetric Adjustments of Rating Curves
Recent Advances in Remote Sensing and Modeling of Flood Inundation III Poster
Benchmark Flood Inundation Mapping Using RGB Aerial Imagery and a Sub-Matrix Convolutional Neural Network
Bridging Return Period Gaps in Flood Inundation Mapping Using a Hybrid Deep Learning Approach
Generation of High-Resolution Flood Inundation Maps from Airborne Imagery Using Supervised Machine Learning
Stage-Specific Intercomparison of Five Flood Inundation Models Across the Rising and Falling Limbs of a Flood Event
Improving NOAA-OWP HAND Flood Depth Estimation with Machine Learning-Based Surrogate Modeling
Automated Extraction of River Channels and Morphological Attributes from SAR Imagery Using a Fine-Tuned Deep Learning Foundation Model and Computer Vision Post-Processing Algorithms
Rise of the Guadalupe River: A Multifaceted post-event Analysis of the July 2025 Texas Flood event
A Decade of Impact: The Water Prediction Innovators Summer Institute
A Framework for the Evaluation of Flood Inundation Predictions Over Extensive Benchmark Databases
Bankfull and Mean-Flow Channel Geometry Estimation Through Machine Learning Algorithms Across the CONtiguous United States (CONUS)
A Neural Network-Based Integration of HEC-RAS, LISFLOOD-FP, and OWP-HAND FIM for Enhanced Flood Inundation Mapping
Automated Basin-Scale River Reach Segmentation using Morphologic Attributes Derived from Sentinel-1 SAR and SAM2 Deep Learning Foundation Model
Remote Sensing-Based Mapping and Monitoring Salinity and Dissolved Oxygen in Mobile Bay and Coastal Alabama Using Deep Learning and Sentinel‑3 OLCI Data

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