Dakota Dunes, SD
Dakota Dunes, SD's wildfire risk, in USFS's own numbers
USFS scores Dakota Dunes at the 77th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 1,247 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 Dakota Dunes at the 74th percentile, close to its 77th-percentile risk score.
What "at risk" means for the buildings here
Dakota Dunes rates 84.4% Minimal exposure against just 15.6% Direct and 0% Indirect — of 1,247 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Dakota Dunes against the rest of the country
Dakota Dunes scores 77th nationally and 75th 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, Dakota Dunes ranks 7,320 for wildfire risk (1 is highest) and 10,365 by building count (1 is largest). Within South Dakota alone, it ranks 109 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
Shopping for coverage in Dakota Dunes
Dakota Dunes's high rating (77th 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.
Lowering exposure, not just insuring around it
Dakota Dunes's 84.4% 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 Dakota Dunes's figures come from
Dakota Dunes's 77th-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 Dakota Dunes's dominant minimal exposure actually means, with real examples from across the dataset.