Garvin, OK
How exposed is Garvin to wildfire?
USFS scores Garvin at the 79th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 147 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Garvin at the 81st national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Garvin's buildings actually sit
Of Garvin's 147 counted buildings, 77.6% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Garvin against the rest of the country
Garvin's 79th national percentile looks worse in isolation than its 18th ranking inside Oklahoma does — this place is on the milder end for its own state, by 61 points. Among the 31,521 US communities USFS scores, Garvin ranks 6,784 for wildfire risk (1 is highest) and 27,000 by building count (1 is largest). Within Oklahoma alone, it ranks 687 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Garvin and the insurance market
Garvin's 79th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Garvin
Garvin's 77.6% 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 Garvin's figures come from
Every one of the two percentiles behind Garvin's 6,784-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Garvin's dominant direct exposure actually means, with real examples from across the dataset.