High Resolution Flood Extent Detection Using Deep Learning with Random Forest Derived Training Labels

1. 1Collect high-frequency, high-resolution optical imagery from sources like PlanetScope
2. 2Use Random Forest to derive training labels for flood extent detection
3. 3Train a deep learning model using the derived training labels
4. 4Validate the model using limited observations during extreme events

Data scientists and AI engineers on a team can benefit from this research as it provides a novel approach to flood mapping, which can be applied to various disaster response and risk mitigation scenarios

💡 Random Forest can be used to derive training labels for deep learning-based flood extent detection

💡 Deep learning + Random Forest for high-res flood mapping