Babbitt, MN
Babbitt wildfire risk explained
Babbitt sits at the 76th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 1,236 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Babbitt at the 72nd national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Babbitt's building exposure, zone by zone
1,236 buildings are counted in Babbitt, and 72% of them are Indirect exposure — ember-driven risk rather than the 28% in Direct exposure or the 0% rated Minimal.
Where Babbitt ranks
Babbitt's 96th-percentile standing inside Minnesota outpaces its 76th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Babbitt ranks 7,690 for wildfire risk (1 is highest) and 10,433 by building count (1 is largest). Within Minnesota alone, it ranks 36 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
Babbitt and the insurance market
Babbitt's 76th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Babbitt's 72% 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 Babbitt's figures come from
Every one of the two percentiles behind Babbitt's 7,690-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Babbitt's dominant indirect exposure actually means, with real examples from across the dataset.