On your question about deterministic vs LLM-driven: I'd lean toward keeping the spatial indexing, deduplication, and basic threshold logic deterministic. Those are well-defined problems with known-good algorithms. The LLM adds value where you're synthesizing ambiguous evidence — "is this cluster of weak FIRMS detections near a known industrial site, or is it a new start in timber?" That kind of contextual reasoning is hard to codify as rules.

One operational question: have you thought about how this integrates with existing incident management workflows? Wildland fire teams run everything through ICS structures and often have limited connectivity on the fireline. Being able to push a structured alert (lat/lon, confidence level, fuel type, weather conditions) into their existing tools would be a big deal for adoption.

The dataset includes US coverage but it's not filtered the same way and FAR more noisy, so I appreciate efforts like this. We haven't got there yet but if you were looking for something deterministic and automatable the Canadian gov's process is potentially worth learning about.

They also produce perimeter estimates based on the hotspots which we can extract and put into a physics-based fire growth model like Prometheus or FARSITE to estimate future fire behaviour based on forecasted weather. This gives very actionable and deterministic estimates of future fire behaviour. We also have worked on a risk model that determines the likelihood of that future fire growth interacting with various assets on the landscape (urban interface areas, power lines, fuel pipelines, forest inventory, etc) and calls out high risk areas. One thing we've been wondering if where LLMs fit into any of this (if at all) so appreciate seeing what others are doing.

Small nit: don't name incidents until you have the official name. It could cause confusion once it is named.

Instead, something like "New detection near Colusa" or "New incident 10 mi NW of Colusa".

curious about the 23 tools though -- are those all invoked through one Gemini orchestration pass or is there a routing layer picking which subset to call per detection? feels like that'd stack up fast latency-wise

When checking the Evidence tab for data that supports the conclusion that there could be a fire in progress I found that it could be improved by excluding the evidence posts for all the mapped fire locations except the one that the user clicked. Presently, if you click that Evidence tab you get a roll of links to posts or mentions or whatever for every fire. I believe that a user would most appreciate data that pertains to the fire they are trying to monitor.

I am not a fan of grey text. It does not improve site navigability or usability and it can get lost in screen glare unless bold grey text is used. It would still be grey text though and I am still not a fan. Perhaps shades of blue or yellow to contrast with the black bar.

Example in case you are thinking of modifying the page - Your top frame has the ap name "SIGNET" in white capitals. Right next to that is an orange dot, probably to signify that something is happening or that the site is "LIVE". Notice that "LIVE" is not only in grey text, beside an orange dot which will be the eyeball magnet, but it is also a smaller font than the ap name "SIGNET".

From my perspective, the site would be improved by changing grey text to a more contrasting color and asking the question - "What information should be the most important topic on this page?" In that way you can optimize it for your users.

Before posting this comment I went back to check that the points I hoped to make were valid points. It turns out that not all "Evidence" links have evidence for every fire on the map. I randomly chose the Custer County Incident when I checked that and found all sorts of stuff pertaining to Texas fires. Perhaps this is not a huge problem for you to solve. I checked the Rapides Parish Incident in Lousyana and it only has data about that event.

Maybe some cleaning of links is in order.