Livingston, MT
How exposed is Livingston to wildfire?
USFS scores Livingston at the 87th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 4,622 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Livingston at the 87th percentile, close to its 87th-percentile risk score.
What "at risk" means for the buildings here
4,622 buildings are counted in Livingston, and 94.4% of them are Indirect exposure — ember-driven risk rather than the 5.6% in Direct exposure or the 0% rated Minimal.
Livingston against the rest of the country
Livingston ranks lower within Montana (68th percentile statewide) than its 87th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Livingston ranks 4,005 for wildfire risk (1 is highest) and 3,677 by building count (1 is largest). Within Montana alone, it ranks 151 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
Livingston and the insurance market
At the 87th percentile nationally, Livingston carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
Livingston's 94.4% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Livingston's figures come from
Livingston's 87th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Livingston's dominant indirect exposure actually means, with real examples from across the dataset.