Sure, it’s all about turning chaos into numbers. Fire crests can be recorded with acoustic sensors that log decibel levels, and you can combine that with satellite‑based thermal imaging to map the intensity across a landscape. Once you plot the decibel readings over time and overlay the heat maps, the roar becomes a time‑series curve with peaks that line up with the fire’s front. The trick is syncing the audio timestamps with the satellite passes—otherwise you end up with a jumbled dataset. If you pull the data together cleanly, you’ll see patterns like the “wave” of intensity as the fire spreads, which can even feed into predictive models. Think of it as turning a roaring inferno into a set of tidy, analyzable points.

You’ll get a neat dataset if you keep the sensors on schedule, but I’ll leave the actual fire to the specialists—my job is to make sure the numbers don’t start a new blaze.