Frankfort, SD
Frankfort, SD's wildfire risk, in USFS's own numbers
USFS scores Frankfort at the 50th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 192 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 Frankfort at the 45th percentile, close to its 50th-percentile risk score.
Where Frankfort's buildings actually sit
58.3% of Frankfort's 192 buildings sit in USFS's Direct exposure zone, roughly 112 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 41.7% are Minimal.
How Frankfort compares
Inside South Dakota, Frankfort sits at just the 29th percentile even though it scores 50th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Frankfort ranks 15,864 for wildfire risk (1 is highest) and 25,175 by building count (1 is largest). Within South Dakota alone, it ranks 311 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 50th national percentile, Frankfort rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Frankfort (58.3%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Frankfort's figures come from
Every one of the two percentiles behind Frankfort's 15,864-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Frankfort's dominant direct exposure actually means, with real examples from across the dataset.