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Thomas Oommen
University of Mississippi Main CampusMeeting roles in:
Linking Ground Displacement and Moisture Estimates at Tailings Impoundments Using Sentinel-1 SAR Data
Uncovering Levee Failures: Remote Sensing Approaches for Early Detection
Evaluating the Sensitivity of GRACE/GRACE-FO in Detecting Potential Saline Water Intrusion Zones
Beyond Proxies: A Data-Driven Framework for Mapping Nitrogen and Phosphorus in Surface Waters
Simulating Future Landslide Hazards Under Extreme Rainfall Using Process-Based and Stochastic Modeling
Slope Instability Predictor-Kerala (SLIP-K): A mobile/web application for landslide hazard prediction in Idukki, India
Using InSAR-Derived Subsidence to Guide Well Placement for Hydraulic Characterization
Near-Real-Time Soil Moisture Prediction Using Thermal Remote Sensing And Machine Learning
Enter Note
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