Minong, WI
How exposed is Minong to wildfire?
Minong sits at the 47th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 515 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Minong at the 46th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Indirect exposure is dominant in Minong (61.4% of 515 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 38.6% sit in the Direct zone.
Where Minong ranks
Within Wisconsin, Minong ranks higher (97th percentile) than it does nationally (47th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Minong ranks 16,659 for wildfire risk (1 is highest) and 17,114 by building count (1 is largest). Within Wisconsin alone, it ranks 23 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Minong and the insurance market
Minong's elevated rating (47th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Minong's 61.4% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Minong's figures come from
Every one of the two percentiles behind Minong's 16,659-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Minong's dominant indirect exposure actually means, with real examples from across the dataset.