Coal Fork, WV
How exposed is Coal Fork to wildfire?
USFS scores Coal Fork at the 92nd national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 726 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Coal Fork at the 93rd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Coal Fork's building exposure, zone by zone
Of Coal Fork's 726 counted buildings, 87.3% 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.
Where Coal Fork ranks
Coal Fork's risk sits at a similar level relative to West Virginia (87th percentile statewide) as it does nationally (92nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Coal Fork ranks 2,537 for wildfire risk (1 is highest) and 14,387 by building count (1 is largest). Within West Virginia alone, it ranks 56 of 429 places by risk. See the full county-by-county picture for West Virginia on its state page.
Coal Fork and the insurance market
Coal Fork's very high rating (92nd percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
With 87.3% of Coal Fork in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Coal Fork's figures come from
The methodology guide shows exactly how USFS turned 726 counted buildings into the percentiles shown above for Coal Fork. The exposure-zones guide covers what Coal Fork's dominant direct exposure actually means, with real examples from across the dataset.