Fairview, TX
Fairview wildfire risk explained
USFS scores Fairview at the 63rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 3,983 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 Fairview at the 63rd percentile, close to its 63rd-percentile risk score.
Fairview's building exposure, zone by zone
Of Fairview's 3,983 counted buildings, 46% carry Direct exposure and only 17.4% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
How Fairview compares
Fairview ranks lower within Texas (18th percentile statewide) than its 63rd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Fairview ranks 11,832 for wildfire risk (1 is highest) and 4,266 by building count (1 is largest). Within Texas alone, it ranks 1,475 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Fairview and the insurance market
Fairview's 63rd-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.
What would actually reduce this score
Because Direct exposure dominates in Fairview (46%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Fairview's figures come from
Every one of the two percentiles behind Fairview's 11,832-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Fairview's dominant direct exposure actually means, with real examples from across the dataset.