Hales Corners, WI
Hales Corners wildfire risk explained
Hales Corners's 3,014 buildings earn a 26th-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Hales Corners at the 29th percentile, close to its 26th-percentile risk score.
What "at risk" means for the buildings here
Only 29.1% of Hales Corners's 3,014 buildings carry Direct exposure and 0% carry Indirect; the remaining 70.9% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Hales Corners against the rest of the country
Within Wisconsin, Hales Corners ranks higher (51st percentile) than it does nationally (26th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Hales Corners ranks 23,499 for wildfire risk (1 is highest) and 5,415 by building count (1 is largest). Within Wisconsin alone, it ranks 401 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Hales Corners and the insurance market
Hales Corners's moderate wildfire rating (26th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Hales Corners
Even with 70.9% of Hales Corners 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 Hales Corners's figures come from
The methodology guide shows exactly how USFS turned 3,014 counted buildings into the percentiles shown above for Hales Corners. The exposure-zones guide covers what Hales Corners's dominant minimal exposure actually means, with real examples from across the dataset.