Kearney, MO
Kearney, MO's wildfire risk, in USFS's own numbers
USFS scores Kearney at the 63rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 4,034 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Kearney's burn probability — fire likelihood with no building count factored in — sits at the 64th percentile nationally.
What "at risk" means for the buildings here
76.7% of Kearney's 4,034 buildings sit in USFS's Minimal exposure zone, with only 22.9% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
How Kearney compares
There's little gap between Kearney's 63rd national percentile and its 62nd percentile inside Missouri, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Kearney ranks 11,786 for wildfire risk (1 is highest) and 4,208 by building count (1 is largest). Within Missouri alone, it ranks 401 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
What this risk score means for insurance
Kearney's 63rd-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.
Hardening a home in Kearney
Kearney's 76.7% 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 Kearney's figures come from
Kearney's 63rd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Kearney's dominant minimal exposure actually means, with real examples from across the dataset.