In response to the recent California fires, we’re launching a new, highly experimental layer: live fire detections from the GOES 17 (West) satellite.
GOES 16 and 17 are geostationary satellites positioned over the eastern US (16) and western US (17), streaming images back to Earth on a near-real-time basis. You’ve probably seen their imagery used for animated loops of hurricanes and other large-scale weather events. In addition to raw multi-spectral imagery, NOAA also releases a number of derived datasets, one of which is active fire detections. In the daytime, these fire detections are reported at 5 minute intervals.
The good news: Live updates. In addition to the satellite’s rapid update interval, the CalTopo map layer will auto-refresh to ensure you are always looking at the most current information, and the time of the last satellite image is displayed on the layer. For new or rapidly moving fires, this can be useful information to supplement between MODIS and VIIRS satellites passes from the “fire activity” layer.
The bad news: each pixel is roughly 2km by 2km, so the layer will only show larger fire activity. And an error of a single pixel is enough to place a fire over a mile off from its true location – this is not a layer that will give you insight down to the level of whether a specific neighborhood has burned. The “fire activity” layer is better for that use case, although even that is still a very imprecise tool that only reports approximate locations and is easy to over-interpret as having more precision than it does.
We are currently pulling data only from the GOES-17 (West) satellite, so the layer only provides coverage for the western US. We hope to integrate GOES-16 (East) soon, in addition to providing other GOES data such as imagery.
GOES has been on our “someday” task list for a while, but with the developing fires, the CalTopo team threw this layer together from scratch in under 72 hours. In normal times, we would spend considerably longer testing this layer internally, both to find bugs and adjust the way data is displayed. Be aware that there may be undiscovered bugs, and that the layer will likely undergo some significant changes in the next few weeks.