Erlanger, KY
Erlanger wildfire risk explained
USFS's Wildfire Risk to Communities model puts Erlanger at the 12th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 6,742 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Erlanger's burn probability — fire likelihood with no building count factored in — sits at the 13th percentile nationally.
What "at risk" means for the buildings here
6,742 buildings are counted in Erlanger, and 42.1% of them are Indirect exposure — ember-driven risk rather than the 29.2% in Direct exposure or the 28.7% rated Minimal. At 6,742 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
How Erlanger compares
Erlanger scores 12th nationally and 16th 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, Erlanger ranks 27,884 for wildfire risk (1 is highest) and 2,567 by building count (1 is largest). Within Kentucky alone, it ranks 466 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
Erlanger and the insurance market
Erlanger's low wildfire rating (12th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Erlanger (42.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Erlanger's figures come from
The methodology guide shows exactly how USFS turned 6,742 counted buildings into the percentiles shown above for Erlanger. The exposure-zones guide covers what Erlanger's dominant indirect exposure actually means, with real examples from across the dataset.