Burnett, WI
Burnett, WI's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Burnett at the 51st national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 163 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Burnett at the 53rd national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Indirect exposure is dominant in Burnett (69.3% of 163 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 30.7% sit in the Direct zone.
Burnett against the rest of the country
Burnett's 99th-percentile standing inside Wisconsin outpaces its 51st national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Burnett ranks 15,430 for wildfire risk (1 is highest) and 26,309 by building count (1 is largest). Within Wisconsin alone, it ranks 13 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
At the 51st national percentile, Burnett rates elevated 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
Because 69.3% of Burnett's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Burnett's figures come from
Every one of the two percentiles behind Burnett's 15,430-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Burnett's dominant indirect exposure actually means, with real examples from across the dataset.