Henriette, MN
Henriette, MN's wildfire risk, in USFS's own numbers
Henriette sits at the 65th 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 83 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Henriette at the 66th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Henriette's building exposure, zone by zone
Direct exposure dominates in Henriette: 69.9% of its 83 buildings, versus 30.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Henriette against the rest of the country
Compare Henriette's two percentiles: 90th within Minnesota, only 65th nationally — a gap of 25 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Henriette ranks 11,060 for wildfire risk (1 is highest) and 29,762 by building count (1 is largest). Within Minnesota alone, it ranks 91 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
Henriette and the insurance market
Henriette's high rating (65th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
With 69.9% of Henriette in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Henriette's figures come from
The methodology guide shows exactly how USFS turned 83 counted buildings into the percentiles shown above for Henriette. The exposure-zones guide covers what Henriette's dominant direct exposure actually means, with real examples from across the dataset.