Florence, SD
Florence, SD's wildfire risk, in USFS's own numbers
USFS scores Florence at the 44th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 254 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 Florence at the 42nd percentile, close to its 44th-percentile risk score.
What "at risk" means for the buildings here
Only 31.5% of Florence's 254 buildings carry Direct exposure and 0% carry Indirect; the remaining 68.5% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Florence against the rest of the country
Florence ranks lower within South Dakota (20th percentile statewide) than its 44th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Florence ranks 17,537 for wildfire risk (1 is highest) and 23,030 by building count (1 is largest). Within South Dakota alone, it ranks 353 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 44th national percentile, Florence rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With 68.5% of buildings rated Minimal exposure, Florence gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Florence's figures come from
The methodology guide shows exactly how USFS turned 254 counted buildings into the percentiles shown above for Florence. The exposure-zones guide covers what Florence's dominant minimal exposure actually means, with real examples from across the dataset.