Pine Knot, KY
How exposed is Pine Knot to wildfire?
USFS scores Pine Knot at the 86th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 928 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Pine Knot at the 89th national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Pine Knot's buildings actually sit
Direct exposure dominates in Pine Knot: 73.8% of its 928 buildings, versus 26.2% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Pine Knot ranks
There's little gap between Pine Knot's 86th national percentile and its 87th percentile inside Kentucky, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Pine Knot ranks 4,321 for wildfire risk (1 is highest) and 12,488 by building count (1 is largest). Within Kentucky alone, it ranks 74 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
Shopping for coverage in Pine Knot
Pine Knot's very high rating (86th 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
Pine Knot's 73.8% 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 Pine Knot's figures come from
Every one of the two percentiles behind Pine Knot's 4,321-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Pine Knot's dominant direct exposure actually means, with real examples from across the dataset.