Using machine learning and radar to better understand storm surge risk
The types of land around us play an important role in how major storms will unfold -- flood waters may travel differently over rural versus urban areas, for example. However, it's challenging to get an accurate picture of land types using only satellite image data because it is so difficult to interpret.
Researchers at the Cockrell School of Engineering have, for the first time, applied a machine learning algorithm to measure the surface roughness of different types of land with a high level of detail. The team used a type of satellite imagery that is more dependable and easier to capture than typical optical photographs but also more challenging to analyze. And they are working to integrate this data into storm surge models to give a clearer ...








