Asher, OK
How exposed is Asher to wildfire?
Asher sits at the 92nd percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 305 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Asher at the 93rd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Asher's buildings actually sit
USFS classifies 67.2% of Asher's buildings as Direct exposure, higher than its 32.8% Indirect share and far above its 0% Minimal share — a profile where 205 structures sit close enough to vegetation that lot clearing matters most.
How Asher compares
Asher's 92nd national percentile looks worse in isolation than its 58th ranking inside Oklahoma does — this place is on the milder end for its own state, by 34 points. Among the 31,521 US communities USFS scores, Asher ranks 2,492 for wildfire risk (1 is highest) and 21,509 by building count (1 is largest). Within Oklahoma alone, it ranks 345 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Shopping for coverage in Asher
At the 92nd percentile nationally, Asher 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 Asher
Asher's 67.2% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Asher's figures come from
Every one of the two percentiles behind Asher's 2,492-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Asher's dominant direct exposure actually means, with real examples from across the dataset.