Cedarburg, WI
How exposed is Cedarburg to wildfire?
USFS scores Cedarburg at the 25th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 4,662 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Cedarburg's burn probability — fire likelihood with no building count factored in — sits at the 26th percentile nationally.
Cedarburg's building exposure, zone by zone
USFS classifies 86.3% of Cedarburg's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 13.6% Direct and 0.1% Indirect — a landscape-level risk rather than a building-by-building one.
How Cedarburg compares
Within Wisconsin, Cedarburg ranks higher (50th percentile) than it does nationally (25th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Cedarburg ranks 23,593 for wildfire risk (1 is highest) and 3,649 by building count (1 is largest). Within Wisconsin alone, it ranks 407 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Shopping for coverage in Cedarburg
At the 25th national percentile, Cedarburg rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Even with 86.3% of Cedarburg 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 Cedarburg's figures come from
Every one of the two percentiles behind Cedarburg's 23,593-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Cedarburg's dominant minimal exposure actually means, with real examples from across the dataset.