Kenwood, OK
Kenwood, OK's wildfire risk, in USFS's own numbers
Kenwood sits at the 91st 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 697 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Kenwood at the 93rd percentile, close to its 91st-percentile risk score.
Where Kenwood's buildings actually sit
USFS classifies 95.6% of Kenwood's buildings as Direct exposure, higher than its 4.5% Indirect share and far above its 0% Minimal share — a profile where 666 structures sit close enough to vegetation that lot clearing matters most.
Kenwood against the rest of the country
Kenwood's 91st national percentile looks worse in isolation than its 50th ranking inside Oklahoma does — this place is on the milder end for its own state, by 41 points. Among the 31,521 US communities USFS scores, Kenwood ranks 3,000 for wildfire risk (1 is highest) and 14,693 by building count (1 is largest). Within Oklahoma alone, it ranks 418 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Shopping for coverage in Kenwood
At the 91st percentile nationally, Kenwood 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 Kenwood
Because Direct exposure dominates in Kenwood (95.6%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Kenwood's figures come from
The methodology guide shows exactly how USFS turned 697 counted buildings into the percentiles shown above for Kenwood. The exposure-zones guide covers what Kenwood's dominant direct exposure actually means, with real examples from across the dataset.