Floods can cause serious damage to homes, farms, and cities. To help respond to these disasters faster, we developed a method using satellite images to detect where flooding has occurred. We tested this approach using a real flood event from 2018 in North Carolina. By comparing satellite images taken before and after the flood, we could clearly see which areas were underwater. We then compared these flooded areas with land use maps to find out how different types of land—like farmland or forests—were affected.

This method uses free software and satellite data and is partly automated, making it faster and easier to use in the future. We also plan to connect this method with weather prediction tools from NOAA to help detect floods earlier. Our goal is to create a tool that can be used quickly after a storm to identify flooded areas and measure the damage. This could help emergency teams, local governments, and the public get better information when they need it most.