WildfireRiskFinder

Albion, MI

Albion, MI's wildfire risk, in USFS's own numbers

Low
9thpercentile nationally

Albion's 3,545 buildings earn a 9th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Albion at the 9th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Albion's buildings actually sit

3,545Total buildings
11.4%Direct exposure
34.4%Indirect exposure
54.2%Minimal exposure

Albion rates 54.2% Minimal exposure against just 11.4% Direct and 34.4% Indirect — of 3,545 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

Albion against the rest of the country

Within Michigan, Albion ranks higher (28th percentile) than it does nationally (9th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Albion ranks 28,682 for wildfire risk (1 is highest) and 4,724 by building count (1 is largest). Within Michigan alone, it ranks 532 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.

Shopping for coverage in Albion

Albion's low rating (9th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Albion

Even with 54.2% of Albion 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 Albion's figures come from

The methodology guide shows exactly how USFS turned 3,545 counted buildings into the percentiles shown above for Albion. The exposure-zones guide covers what Albion's dominant minimal exposure actually means, with real examples from across the dataset.