Kadoka, SD
How exposed is Kadoka to wildfire?
USFS's Wildfire Risk to Communities model puts Kadoka at the 76th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 535 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Kadoka at the 74th percentile, close to its 76th-percentile risk score.
Where Kadoka's buildings actually sit
88% of Kadoka's 535 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 12% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Kadoka against the rest of the country
Kadoka scores 76th nationally and 74th within South Dakota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Kadoka ranks 7,480 for wildfire risk (1 is highest) and 16,806 by building count (1 is largest). Within South Dakota alone, it ranks 113 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
What this risk score means for insurance
At the 76th percentile nationally, Kadoka 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 ember exposure the dominant pattern in Kadoka (88% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Kadoka's figures come from
Every one of the two percentiles behind Kadoka's 7,480-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Kadoka's dominant indirect exposure actually means, with real examples from across the dataset.