WildfireRiskFinder

Couderay, WI

Couderay wildfire risk explained

Low
14thpercentile nationally

USFS scores Couderay at the 14th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 122 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Couderay's burn probability — fire likelihood with no building count factored in — sits at the 14th percentile nationally.

What "at risk" means for the buildings here

122Total buildings
79.5%Direct exposure
20.5%Indirect exposure
0%Minimal exposure

122 buildings are counted in Couderay, and 79.5% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.

Where Couderay ranks

Couderay scores 14th nationally and 14th within Wisconsin — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Couderay ranks 27,154 for wildfire risk (1 is highest) and 28,090 by building count (1 is largest). Within Wisconsin alone, it ranks 693 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.

What this risk score means for insurance

Couderay's low rating (14th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Lowering exposure, not just insuring around it

Couderay's 79.5% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.

Where Couderay's figures come from

Couderay's 14th-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 Couderay's dominant direct exposure actually means, with real examples from across the dataset.