WildfireRiskFinder

Scammon, KS

Scammon wildfire risk explained

Elevated
48thpercentile nationally

USFS scores Scammon at the 48th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 338 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Scammon's burn probability — fire likelihood with no building count factored in — sits at the 49th percentile nationally.

Where Scammon's buildings actually sit

338Total buildings
29%Direct exposure
0%Indirect exposure
71%Minimal exposure

71% of Scammon's 338 buildings sit in USFS's Minimal exposure zone, with only 29% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.

Scammon against the rest of the country

Scammon's 48th national percentile looks worse in isolation than its 27th ranking inside Kansas does — this place is on the milder end for its own state, by 21 points. Among the 31,521 US communities USFS scores, Scammon ranks 16,447 for wildfire risk (1 is highest) and 20,628 by building count (1 is largest). Within Kansas alone, it ranks 526 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.

Shopping for coverage in Scammon

Scammon's elevated wildfire rating (48th 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 Scammon

Scammon's 71% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.

Where Scammon's figures come from

The methodology guide shows exactly how USFS turned 338 counted buildings into the percentiles shown above for Scammon. The exposure-zones guide covers what Scammon's dominant minimal exposure actually means, with real examples from across the dataset.