Brighton, UT
Brighton, UT's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Brighton lands at the 97th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 760 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Brighton at the 96th percentile, close to its 97th-percentile risk score.
What "at risk" means for the buildings here
Direct exposure dominates in Brighton: 97.6% of its 760 buildings, versus 2.4% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Brighton compares
Brighton's risk sits at a similar level relative to Utah (90th percentile statewide) as it does nationally (97th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Brighton ranks 929 for wildfire risk (1 is highest) and 14,023 by building count (1 is largest). Within Utah alone, it ranks 35 of 326 places by risk. See the full county-by-county picture for Utah on its state page.
Shopping for coverage in Brighton
At the 97th percentile nationally, Brighton 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.
Hardening a home in Brighton
With 97.6% of Brighton in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Brighton's figures come from
Brighton's 97th-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 Brighton's dominant direct exposure actually means, with real examples from across the dataset.