Emergency crews responding to hurricane-damaged areas may soon get an assist from a machine learning model that can better predict the extent of building damage soon after the storm passes. The model uses remote sensing from satellites that can generate building footprints from pre-hurricane images and then compare them with images taken after the storm. While some previous models could only tell if a building was damaged or not damaged, this deep learning model can accurately classify how much damage buildings sustained—key information for emergency responders, said Desheng Liu, co-author of the study and professor of geography at The Ohio State University.
