Eyota, MN
How exposed is Eyota to wildfire?
Eyota sits at the 3rd percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 976 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Eyota at the 3rd national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Eyota's buildings actually sit
Only 10.9% of Eyota's 976 buildings carry Direct exposure and 0% carry Indirect; the remaining 89.1% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
How Eyota compares
Eyota's risk sits at a similar level relative to Minnesota (5th percentile statewide) as it does nationally (3rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Eyota ranks 30,489 for wildfire risk (1 is highest) and 12,099 by building count (1 is largest). Within Minnesota alone, it ranks 868 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
Eyota and the insurance market
Eyota's low wildfire rating (3rd 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 89.1% of Eyota 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 Eyota's figures come from
Eyota's 3rd-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 Eyota's dominant minimal exposure actually means, with real examples from across the dataset.