Lane, SD
Lane, SD's wildfire risk, in USFS's own numbers
Lane sits at the 51st percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 114 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Lane at the 50th percentile, close to its 51st-percentile risk score.
What "at risk" means for the buildings here
50.9% of Lane's 114 buildings sit in USFS's Minimal exposure zone, with only 47.4% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Lane against the rest of the country
Lane's 51st national percentile looks worse in isolation than its 31st ranking inside South Dakota does — this place is on the milder end for its own state, by 20 points. Among the 31,521 US communities USFS scores, Lane ranks 15,612 for wildfire risk (1 is highest) and 28,475 by building count (1 is largest). Within South Dakota alone, it ranks 304 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 51st national percentile, Lane rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Lane
With 50.9% of buildings rated Minimal exposure, Lane gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Lane's figures come from
Every one of the two percentiles behind Lane's 15,612-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Lane's dominant minimal exposure actually means, with real examples from across the dataset.