Kilkenny, MN
How exposed is Kilkenny to wildfire?
Kilkenny sits at the 33rd percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 121 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Kilkenny at the 28th percentile, close to its 33rd-percentile risk score.
What "at risk" means for the buildings here
Indirect exposure is dominant in Kilkenny (74.4% of 121 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 25.6% sit in the Direct zone.
Kilkenny against the rest of the country
Kilkenny's risk sits at a similar level relative to Minnesota (40th percentile statewide) as it does nationally (33rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Kilkenny ranks 21,112 for wildfire risk (1 is highest) and 28,111 by building count (1 is largest). Within Minnesota alone, it ranks 544 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
Kilkenny and the insurance market
At the 33rd national percentile, Kilkenny rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With ember exposure the dominant pattern in Kilkenny (74.4% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Kilkenny's figures come from
Every one of the two percentiles behind Kilkenny's 21,112-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Kilkenny's dominant indirect exposure actually means, with real examples from across the dataset.