Wayland, KY
Wayland, KY's wildfire risk, in USFS's own numbers
USFS scores Wayland at the 93rd national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 254 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Wayland at the 95th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Direct exposure dominates in Wayland: 75.6% of its 254 buildings, versus 24.4% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Wayland against the rest of the country
Wayland scores 93rd nationally and 97th within Kentucky — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Wayland ranks 2,173 for wildfire risk (1 is highest) and 23,012 by building count (1 is largest). Within Kentucky alone, it ranks 19 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
Wayland and the insurance market
At the 93rd percentile nationally, Wayland carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Wayland's 75.6% 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 Wayland's figures come from
Every one of the two percentiles behind Wayland's 2,173-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Wayland's dominant direct exposure actually means, with real examples from across the dataset.