Munising, MI
Munising wildfire risk explained
USFS scores Munising at the 23rd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 1,350 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Munising at the 23rd national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Munising's building exposure, zone by zone
Most of Munising's buildings (73.9%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Munising ranks
Within Michigan, Munising ranks higher (72nd percentile) than it does nationally (23rd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Munising ranks 24,237 for wildfire risk (1 is highest) and 9,829 by building count (1 is largest). Within Michigan alone, it ranks 209 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Munising and the insurance market
Munising's moderate wildfire rating (23rd 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.
What would actually reduce this score
Munising's 73.9% 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 Munising's figures come from
The methodology guide shows exactly how USFS turned 1,350 counted buildings into the percentiles shown above for Munising. The exposure-zones guide covers what Munising's dominant indirect exposure actually means, with real examples from across the dataset.