Golden, MO
Golden, MO's wildfire risk, in USFS's own numbers
USFS scores Golden at the 73rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 415 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 Golden at the 76th percentile, close to its 73rd-percentile risk score.
Where Golden's buildings actually sit
415 buildings are counted in Golden, and 97.4% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 2.7% rated Minimal.
Golden against the rest of the country
Golden's risk sits at a similar level relative to Missouri (87th percentile statewide) as it does nationally (73rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Golden ranks 8,637 for wildfire risk (1 is highest) and 18,927 by building count (1 is largest). Within Missouri alone, it ranks 138 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
At the 73rd percentile nationally, Golden carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
With 97.4% of Golden in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Golden's figures come from
Golden's 73rd-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 Golden's dominant direct exposure actually means, with real examples from across the dataset.