Walled Lake, MI
Walled Lake, MI's wildfire risk, in USFS's own numbers
Walled Lake sits at the 10th 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 2,226 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Walled Lake's burn probability — fire likelihood with no building count factored in — sits at the 11th percentile nationally.
Where Walled Lake's buildings actually sit
Walled Lake rates 92.5% Minimal exposure against just 7.6% Direct and 0% Indirect — of 2,226 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Walled Lake against the rest of the country
Compare Walled Lake's two percentiles: 32nd within Michigan, only 10th nationally — a gap of 23 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Walled Lake ranks 28,463 for wildfire risk (1 is highest) and 6,872 by building count (1 is largest). Within Michigan alone, it ranks 503 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Shopping for coverage in Walled Lake
Walled Lake's low rating (10th 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 Walled Lake
Even with 92.5% of Walled Lake 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 Walled Lake's figures come from
Every one of the two percentiles behind Walled Lake's 28,463-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Walled Lake's dominant minimal exposure actually means, with real examples from across the dataset.