Sabetha, KS
Sabetha, KS's wildfire risk, in USFS's own numbers
Sabetha sits at the 77th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 1,472 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Sabetha at the 74th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Sabetha's buildings actually sit
Sabetha rates 87.6% Minimal exposure against just 12.4% Direct and 0% Indirect — of 1,472 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Where Sabetha ranks
There's little gap between Sabetha's 77th national percentile and its 74th percentile inside Kansas, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Sabetha ranks 7,406 for wildfire risk (1 is highest) and 9,299 by building count (1 is largest). Within Kansas alone, it ranks 191 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
Shopping for coverage in Sabetha
Sabetha's 77th-percentile, 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.
What would actually reduce this score
Sabetha's 87.6% 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 Sabetha's figures come from
The methodology guide shows exactly how USFS turned 1,472 counted buildings into the percentiles shown above for Sabetha. The exposure-zones guide covers what Sabetha's dominant minimal exposure actually means, with real examples from across the dataset.