It seems like natural disasters are happening more and more frequently these days. Worse still, we seem ill prepared to deal with them. Even if it’s something we can see coming, like a hurricane, the path to recovery is often a confused mess as first responders scramble to figure out where to allocate resources. Remote sensing technology can help with this, but the current state of the art comes down to comparing aerial before-and-after images from disaster scenes by hand and trying to identify which locations were hit hardest.
To help with this problem, the Defense Innovation Unit (a sort of tech accelerator inside the Department of Defense) is sponsoring a challenge called xView2. Its goal: to develop a computer vision algorithm that can automate the process of detecting and labeling damage based on differences in before-and-after photos. And like all good challenges, there’s a big pile of money at the end for whoever manages to do the best job of it.