Seymour, TX
Seymour wildfire risk explained
USFS scores Seymour at the 80th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 2,107 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Seymour's burn probability — fire likelihood with no building count factored in — sits at the 77th percentile nationally.
Where Seymour's buildings actually sit
Most of Seymour's buildings (90.4%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Seymour against the rest of the country
Seymour's 80th national percentile looks worse in isolation than its 62nd ranking inside Texas does — this place is on the milder end for its own state, by 19 points. Among the 31,521 US communities USFS scores, Seymour ranks 6,254 for wildfire risk (1 is highest) and 7,175 by building count (1 is largest). Within Texas alone, it ranks 693 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
What this risk score means for insurance
At the 80th percentile nationally, Seymour 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.
What would actually reduce this score
Because 90.4% of Seymour'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 Seymour's figures come from
The methodology guide shows exactly how USFS turned 2,107 counted buildings into the percentiles shown above for Seymour. The exposure-zones guide covers what Seymour's dominant indirect exposure actually means, with real examples from across the dataset.