WildfireRiskFinder

Chilton, WI

Chilton wildfire risk explained

Low
14thpercentile nationally

USFS scores Chilton at the 14th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 2,112 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

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

Where Chilton's buildings actually sit

2,112Total buildings
9.9%Direct exposure
0%Indirect exposure
90.1%Minimal exposure

90.1% of Chilton's 2,112 buildings sit in USFS's Minimal exposure zone, with only 9.9% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.

Where Chilton ranks

Chilton's risk sits at a similar level relative to Wisconsin (14th percentile statewide) as it does nationally (14th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Chilton ranks 27,153 for wildfire risk (1 is highest) and 7,160 by building count (1 is largest). Within Wisconsin alone, it ranks 692 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.

Chilton and the insurance market

At the 14th national percentile, Chilton rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

What would actually reduce this score

With 90.1% of buildings rated Minimal exposure, Chilton gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.

Where Chilton's figures come from

The methodology guide shows exactly how USFS turned 2,112 counted buildings into the percentiles shown above for Chilton. The exposure-zones guide covers what Chilton's dominant minimal exposure actually means, with real examples from across the dataset.