Augusta, MT
How exposed is Augusta to wildfire?
USFS's Wildfire Risk to Communities model puts Augusta at the 66th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 370 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Augusta's burn probability — fire likelihood with no building count factored in — sits at the 67th percentile nationally.
What "at risk" means for the buildings here
61.4% of Augusta's 370 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 38.7% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Augusta compares
Inside Montana, Augusta sits at just the 33rd percentile even though it scores 66th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Augusta ranks 10,684 for wildfire risk (1 is highest) and 19,858 by building count (1 is largest). Within Montana alone, it ranks 318 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
What this risk score means for insurance
Augusta's 66th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
Because 61.4% of Augusta's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Augusta's figures come from
The methodology guide shows exactly how USFS turned 370 counted buildings into the percentiles shown above for Augusta. The exposure-zones guide covers what Augusta's dominant indirect exposure actually means, with real examples from across the dataset.