Eaton Rapids, MI
Eaton Rapids, MI's wildfire risk, in USFS's own numbers
Eaton Rapids sits at the 11th 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 2,449 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Eaton Rapids's burn probability — fire likelihood with no building count factored in — sits at the 12th percentile nationally.
Where Eaton Rapids's buildings actually sit
USFS classifies 79.5% of Eaton Rapids's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 20.5% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Eaton Rapids ranks
Eaton Rapids's 39th-percentile standing inside Michigan outpaces its 11th 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, Eaton Rapids ranks 27,930 for wildfire risk (1 is highest) and 6,398 by building count (1 is largest). Within Michigan alone, it ranks 452 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
What this risk score means for insurance
Eaton Rapids's low rating (11th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
Eaton Rapids's 79.5% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Eaton Rapids's figures come from
Eaton Rapids's 11th-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 Eaton Rapids's dominant minimal exposure actually means, with real examples from across the dataset.