Booker, TX
Booker wildfire risk explained
USFS's Wildfire Risk to Communities model puts Booker at the 92nd national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 760 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Booker at the 91st percentile, close to its 92nd-percentile risk score.
Where Booker's buildings actually sit
Most of Booker's buildings (84.7%) 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.
Booker against the rest of the country
Booker's risk sits at a similar level relative to Texas (88th percentile statewide) as it does nationally (92nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Booker ranks 2,657 for wildfire risk (1 is highest) and 14,020 by building count (1 is largest). Within Texas alone, it ranks 210 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in Booker
At the 92nd percentile nationally, Booker 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
Because 84.7% of Booker'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 Booker's figures come from
Every one of the two percentiles behind Booker's 2,657-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Booker's dominant indirect exposure actually means, with real examples from across the dataset.