Cashton, WI
Cashton, WI's wildfire risk, in USFS's own numbers
USFS scores Cashton at the 21st national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 641 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Cashton's burn probability — fire likelihood with no building count factored in — sits at the 22nd percentile nationally.
Cashton's building exposure, zone by zone
Most of Cashton's buildings (85.5%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Cashton ranks
Cashton scores 21st nationally and 36th 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, Cashton ranks 24,820 for wildfire risk (1 is highest) and 15,319 by building count (1 is largest). Within Wisconsin alone, it ranks 520 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Shopping for coverage in Cashton
Cashton's moderate wildfire rating (21st 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.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Cashton (85.5% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Cashton's figures come from
Every one of the two percentiles behind Cashton's 24,820-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Cashton's dominant indirect exposure actually means, with real examples from across the dataset.