Sawyer, KS
How exposed is Sawyer to wildfire?
USFS scores Sawyer at the 97th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 165 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Sawyer at the 96th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
94.6% of Sawyer's 165 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 5.5% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Where Sawyer ranks
Sawyer scores 97th nationally and 98th 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, Sawyer ranks 914 for wildfire risk (1 is highest) and 26,217 by building count (1 is largest). Within Kansas alone, it ranks 13 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
Shopping for coverage in Sawyer
Sawyer's 97th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Sawyer
Because 94.6% of Sawyer'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 Sawyer's figures come from
Every one of the two percentiles behind Sawyer's 914-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Sawyer's dominant indirect exposure actually means, with real examples from across the dataset.