Keota, OK
How exposed is Keota to wildfire?
Keota sits at the 97th 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 375 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Keota at the 99th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Indirect exposure is dominant in Keota (79.2% of 375 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 20.8% sit in the Direct zone.
How Keota compares
There's little gap between Keota's 97th national percentile and its 94th percentile inside Oklahoma, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Keota ranks 952 for wildfire risk (1 is highest) and 19,769 by building count (1 is largest). Within Oklahoma alone, it ranks 53 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
At the 97th percentile nationally, Keota 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
Keota's 79.2% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Keota's figures come from
The methodology guide shows exactly how USFS turned 375 counted buildings into the percentiles shown above for Keota. The exposure-zones guide covers what Keota's dominant indirect exposure actually means, with real examples from across the dataset.