WildfireRiskFinder

Palmer, KS

Palmer, KS's wildfire risk, in USFS's own numbers

High
68thpercentile nationally

USFS's Wildfire Risk to Communities model puts Palmer at the 68th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 131 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Palmer's burn probability — fire likelihood with no building count factored in — sits at the 62nd percentile nationally.

Palmer's building exposure, zone by zone

131Total buildings
36.6%Direct exposure
0%Indirect exposure
63.4%Minimal exposure

Most of Palmer's buildings (63.4% of 131) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.

Where Palmer ranks

Palmer scores 68th nationally and 65th within Kansas — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Palmer ranks 9,952 for wildfire risk (1 is highest) and 27,665 by building count (1 is largest). Within Kansas alone, it ranks 252 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.

Shopping for coverage in Palmer

Palmer's high rating (68th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

Lowering exposure, not just insuring around it

Even with 63.4% of Palmer 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 Palmer's figures come from

The methodology guide shows exactly how USFS turned 131 counted buildings into the percentiles shown above for Palmer. The exposure-zones guide covers what Palmer's dominant minimal exposure actually means, with real examples from across the dataset.