Burlingame, KS
Burlingame, KS's wildfire risk, in USFS's own numbers
USFS scores Burlingame at the 70th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 641 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Burlingame at the 69th percentile, close to its 70th-percentile risk score.
What "at risk" means for the buildings here
71.8% of Burlingame's 641 buildings sit in USFS's Minimal exposure zone, with only 28.2% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
How Burlingame compares
There's little gap between Burlingame's 70th national percentile and its 68th percentile inside Kansas, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Burlingame ranks 9,485 for wildfire risk (1 is highest) and 15,307 by building count (1 is largest). Within Kansas alone, it ranks 236 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
What this risk score means for insurance
Burlingame's high rating (70th 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.
What would actually reduce this score
Even with 71.8% of Burlingame 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 Burlingame's figures come from
The methodology guide shows exactly how USFS turned 641 counted buildings into the percentiles shown above for Burlingame. The exposure-zones guide covers what Burlingame's dominant minimal exposure actually means, with real examples from across the dataset.