Gaining access to high resolution aerial imagery immediately after a disaster like Hurricane Michael is critical for rescue, insurance claims assessment, and humanitarian efforts. The ability to enter an address and instantly see the nearby conditions has obvious benefits. But when the area affected is as large as Michael’s, it is impossible to manually inspect every area. This is where AI and computer vision play an increasingly important role in post-disaster operations.
This makes it possible for an assessor to immediately focus in on a hard hit region. As an example, here is an area in Panama City right in the storms path. Yet not all property sustained equal damage. Here we see a great example of where the model correctly detected light, medium, and high roof damage all in an area roughly the size of a few sports fields. Click here to explore the area shown below in our public map viewer. And a huge thanks to the team at Munich RE for creating this valuable data layer so quickly!