Mahtomedi, MN
Mahtomedi wildfire risk explained
USFS scores Mahtomedi at the 45th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 3,140 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Mahtomedi at the 45th percentile, close to its 45th-percentile risk score.
Where Mahtomedi's buildings actually sit
USFS classifies 62.1% of Mahtomedi's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 37.5% Direct and 0.5% Indirect — a landscape-level risk rather than a building-by-building one.
How Mahtomedi compares
Compare Mahtomedi's two percentiles: 64th within Minnesota, only 45th nationally — a gap of 20 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Mahtomedi ranks 17,425 for wildfire risk (1 is highest) and 5,241 by building count (1 is largest). Within Minnesota alone, it ranks 327 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
Mahtomedi and the insurance market
Mahtomedi's elevated wildfire rating (45th 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
Even with 62.1% of Mahtomedi outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Mahtomedi's figures come from
Mahtomedi's 45th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Mahtomedi's dominant minimal exposure actually means, with real examples from across the dataset.