Phelps, KY
Phelps, KY's wildfire risk, in USFS's own numbers
Phelps sits at the 96th 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 646 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Phelps at the 97th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Phelps's building exposure, zone by zone
USFS classifies 81.4% of Phelps's buildings as Direct exposure, higher than its 18.6% Indirect share and far above its 0% Minimal share — a profile where 526 structures sit close enough to vegetation that lot clearing matters most.
Phelps against the rest of the country
Phelps's risk sits at a similar level relative to Kentucky (100th percentile statewide) as it does nationally (96th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Phelps ranks 1,358 for wildfire risk (1 is highest) and 15,244 by building count (1 is largest). Within Kentucky alone, it ranks 2 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
What this risk score means for insurance
Phelps's very high rating (96th 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
Because Direct exposure dominates in Phelps (81.4%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Phelps's figures come from
Every one of the two percentiles behind Phelps's 1,358-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Phelps's dominant direct exposure actually means, with real examples from across the dataset.