Burneyville, OK
Burneyville, OK's wildfire risk, in USFS's own numbers
USFS scores Burneyville at the 87th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 592 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 Burneyville at the 88th percentile, close to its 87th-percentile risk score.
What "at risk" means for the buildings here
USFS classifies 96.1% of Burneyville's buildings as Direct exposure, higher than its 3.9% Indirect share and far above its 0% Minimal share — a profile where 569 structures sit close enough to vegetation that lot clearing matters most.
How Burneyville compares
Inside Oklahoma, Burneyville sits at just the 36th percentile even though it scores 87th 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, Burneyville ranks 4,199 for wildfire risk (1 is highest) and 15,941 by building count (1 is largest). Within Oklahoma alone, it ranks 534 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
What this risk score means for insurance
Burneyville's very high rating (87th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Burneyville (96.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Burneyville's figures come from
The methodology guide shows exactly how USFS turned 592 counted buildings into the percentiles shown above for Burneyville. The exposure-zones guide covers what Burneyville's dominant direct exposure actually means, with real examples from across the dataset.